Hemp Growing

It was not until early 2012, however, that federal regulations were made consistent with legislative changes. Because of the historic discrimination against farmers of color, and other structural barriers to land ownership for people of color, the population of agricultural producers is already heavily skewed toward white men. Thus, such measures to guarantee FSA committees are representative of agricultural producers in any particular region fall short in their attempts to address the acutely historical causes and outcomes of structural racialization that have upheld white land ownership in particular. The second major channel among the Farm Bill and other federal food and agricultural policies that have played a historic and ongoing role in structural racialization is the Farm Bill’s commodity programs, which have undergirded white farmland ownership at the expense of farmland ownership by people of color. While the FSA lending programs have upheld white farmland ownership amidst increasing consolidation and specialization, the Farm Bill commodity programs uphold white farmland ownership by way of increasing consolidation and The second major channel among the Farm Bill and other federal food and agricultural policies that have played a historic and ongoing role in structural racialization is the Farm Bill’s commodity programs, which have undergirded white farmland ownership at the expense of farmland ownership by people of color. While the FSA lending programs have upheld white farmland ownership amidst increasing consolidation and specialization, the Farm Bill commodity programs uphold white farmland ownership by way of increasing consolidation and The second major channel among the Farm Bill and other federal food and agricultural policies that have played a historic and ongoing role in structural racialization is the Farm Bill’s commodity programs, grow racks with lights which have undergirded white farmland ownership at the expense of farmland ownership by people of color.

While the FSA lending programs have upheld white farmland ownership amidst increasing consolidation and specialization, the Farm Bill commodity programs uphold white farmland ownership by way of increasing consolidation and The third major channel within the Farm Bill and other federal food and agricultural policies that has played a historic and ongoing role in structural racialization is the Farm Bill’s Rural Development programs, which are intended to help strengthen small communities by investing in water systems, housing, new businesses, infrastructure, and similar projects. Because many farms owned by people of color are in counties with little wealth and limited opportunities for non-farm employment, and because many rural and small town communities of color are faced with persistent poverty, Rural Development programs have the potential to promote socio-economic well-being for people of color and other historically marginalized communities. As of 2012, there is a larger percentage of whites in rural communities than in urban communities . Yet, within rural communities, people of color face higher rates of poverty: while only 14% of rural whites live in poverty, 34% of rural Blacks live in poverty. Additionally, as of 2010, Latinos/as, Blacks, and Pacific Islanders have the lowest home ownership rates compared to home ownership rates for whites . Thus, it is unsurprising that, according to a 2013 Tuskegee University study, farmers and rural communities of color have had The third major channel within the Farm Bill and other federal food and agricultural policies that has played a historic and ongoing role in structural racialization is the Farm Bill’s Rural Development programs, which are intended to help strengthen small communities by investing in water systems, housing, new businesses, infrastructure, and similar projects. Because many farms owned by people of color are in counties with little wealth and limited opportunities for non-farm employment, and because many rural and small town communities of color are faced with persistent poverty, Rural Development programs have the potential to promote socio-economic well-being for people of color and other historically marginalized communities.

As of 2012, there is a larger percentage of whites in rural communities than in urban communities . Yet, within rural communities, people of color face higher rates of poverty: while only 14% of rural whites live in poverty, 34% of rural Blacks live in poverty. Additionally, as of 2010, Latinos/as, Blacks, and Pacific Islanders have the lowest home ownership rates compared to home ownership rates for whites. Thus, it is unsurprising that, according to a 2013 Tuskegee University study, farmers and rural communities of color have had PART III OUTLINED HOW LENDING, commodity, and rural development programs have historically undergirded white farmland ownership at the expense of people of color farmland ownership, and how long term changes in the structure of US farmland—the consolidation and specialization of agricultural production, in particular—have exacerbated such trends. Part IV continues this line of argumentation regarding the structure of US farmland and examines how programs geared toward supporting supposedly environmentally sustainable management practices also shape the socio-economic well-being of and farming and rural communities of color relative to white farming and rural communities. First, this part does so by providing a snapshot of the racialized distribution of costs and benefits regarding programs under the conservation title of the Farm Bill . It then outlines the significance of the historical continuity between environmentally-oriented programs and commodity support programs. Finally, it outlines the significance of four federal rural and agricultural support programs in particular—the Conservation Reserve Program , Environmental Quality Incentives Program , organic agriculture programs, and outreach and assistance programs—as well as recent corporate-backed trends in increased bio-fuel production. Part IV argues that, because of their inseparability from commodity crop production, and the consolidation and specialization of agricultural production, and despite the countless environmental benefits they produce, Farm Bill programs under the conservation title also undergird white farmland ownership at the expense of farmland ownership by people of color. Ultimately, they do so by funneling benefits primarily to white large-scale landowners on high quality land and keeping even low quality white-owned farmland profitable—an inadvertent result of the history of farmland ownership in the United States that cannot be seen as separate from the history of racial discrimination.

This part argues, furthermore, that this is the case not only with commodity crop and acreage-based conservation programs , but that management practice-based conservation programs have similar effects. Furthermore, a fourth program, the Outreach and Assistance for Socially Disadvantaged Farmers and Ranchers and Veteran Farmers and Ranchers Program, contributes to the social and economic inequities that characterize commodity and conservation programs alike, yet holds great potential as a strategic rallying point against structural racialization. Finally, Part IV then addresses the relationship between structural racialization, industrial agriculture, environmental degradation, and climate change, and argues that farmers of color and communities of color bear the brunt of such environmental change.PART III OUTLINED HOW LENDING, commodity, and rural development programs have historically undergirded white farmland ownership at the expense of people of color farmland ownership, and how long term changes in the structure of US farmland—the consolidation and specialization of agricultural production, rolling benches for growing in particular—have exacerbated such trends. Part IV continues this line of argumentation regarding the structure of US farmland and examines how programs geared toward supporting supposedly environmentally sustainable management practices also shape the socio-economic well-being of and farming and rural communities of color relative to white farming and rural communities. First, this part does so by providing a snapshot of the racialized distribution of costs and benefits regarding programs under the conservation title of the Farm Bill . It then outlines the significance of the historical continuity between environmentally-oriented programs and commodity support programs. Finally, it outlines the significance of four federal rural and agricultural support programs in particular—the Conservation Reserve Program , Environmental Quality Incentives Program , organic agriculture programs, and outreach and assistance programs—as well as recent corporate-backed trends in increased bio-fuel production. Part IV argues that, because of their inseparability from commodity crop production, and the consolidation and specialization of agricultural production, and despite the countless environmental benefits they produce, Farm Bill programs under the conservation title also undergird white farmland ownership at the expense of farmland ownership by people of color. Ultimately, they do so by funneling benefits primarily to white large-scale landowners on high quality land and keeping even low quality white-owned farmland profitable—an inadvertent result of the history of farmland ownership in the United States that cannot be seen as separate from the history of racial discrimination. This part argues, furthermore, that this is the case not only with commodity crop and acreage-based conservation programs , but that management practice-based conservation programs have similar effects. Furthermore, a fourth program, the Outreach and Assistance for Socially Disadvantaged Farmers and Ranchers and Veteran Farmers and Ranchers Program, contributes to the social and economic inequities that characterize commodity and conservation programs alike, yet holds great potential as a strategic rallying point against structural racialization.

Finally, Part IV then addresses the relationship between structural racialization, industrial agriculture, environmental degradation, and climate change, and argues that farmers of color and communities of color bear the brunt of such environmental change.outlined below, however, maintain the structural benefits historically afforded to whites while keeping people of color at a structural disadvantage.One major Farm Bill conservation program that has undergirded white farmland ownership at the expense of farmland ownership by people of color is the Conservation Reserve Program . The CRP is the largest federal, private-land retirement program in the United States, with 27.5 million acres covered at a cost of $20 billion over the next 10 years. It provides financial compensation for landowners to voluntarily remove land from agricultural production for 10 to 15 years in order to improve soil and water quality and create wildlife habitat. Acres enrolled in CRP have indeed shown a number of environmental gains, including reduced soil erosion, water quality improvements, and wildlife population improvement. However, a number of factors shape the purpose the CRP serves and for whom: first, enrollment is considered to be undesirable by some land owners, primarily because of the cost of compliance and the potential loss of farm income due to the prevention of the use of such land for agricultural production. Thus, as with the 1956 Soil Bank Program from which the CRP grew, it is the least productive land and lowest income households that are often enrolled and kept profitable. Second, studies have shown that conservation compliance does not present a strong economic deterrent for landowners who want to crop former CRP acreage after the CRP term is over, thus highlighting the potentially temporary nature of such economic relief. Third, and perhaps most importantly, only lands planted with commodity crops, especially, corn and wheat are eligible for CRP and not fruits or vegetables, or lands used for livestock. Because white farmers have historically owned large-scale grain and oil seed farmland while farmers of color have been relegated to smaller, non-commodity crop farmland, the Conservation Reserve Program potentially undergirds white farmland ownership, both during times of economic hardship and on marginal land. A 2005 Texas A&M University survey study, for example, found that white landowners were more likely to have land qualified for reserve programs—as well as programs such as the Stewardship Incentives Program and the Forestry Incentives Program . Such landowners not only received more favorable program outreach and assistance, as will be addressed below, they also had more incentives to participate due to the economies of scale and tax savings. Toward this end, the study found that white landowners, on average, were enrolled in the CRP longer and signed up more acres than landowners of color . One major Farm Bill conservation program that has undergirded white farmland ownership at the expense of farmland ownership by people of color is the Conservation Reserve Program . The CRP is the largest federal, private-land retirement program in the United States, with 27.5 million acres covered at a cost of $20 billion over the next 10 years. It provides financial compensation for landowners to voluntarily remove land from agricultural production for 10 to 15 years in order to improve soil and water quality and create wildlife habitat. Acres enrolled in CRP have indeed shown a number of environmental gains, including reduced soil erosion, water quality improvements, and wildlife population improvement. However, a number of factors shape the purpose the CRP serves and for whom: first, enrollment is considered to be undesirable by some land owners, primarily because of the cost of compliance and the potential loss of farm income due to the prevention of the use of such land for agricultural production. 

Toward this end, employers go to great lengths to unlawfully exclude qualified US workers in favor of H-2A workers, many of whom have themselves migrated to the United States during prior seasons. For example, employers schedule interviews at inconvenient times or locations; hire too early in the season, lead workers to arrive for work when there is none; limit their hours in order to discourage them from continuing to work; use employment contracts that demand that workers forfeit their right to sue a grower for lost wages and/or other illegalities; and impose productivity quotas and other unrealistic work demands on employees. These practices greatly discourage US workers from applying to these jobs, which then allows employers to “legally” hire H-2A workers. Additionally, the profits reaped by large agricultural employers and by corporations at all levels of the food system not only come at the expense of the food system worker’s livelihoods and US job loss, but are also subsidized by taxpayers themselves. For example, Walmart, which sells 25% of all the groceries in the United States and is the largest employer in the US and world, has among the lowest wages across the retail industry. Walmart workers cost US taxpayers an estimated $6.2 billion in public assistance that would counteract the consequences of their low wages, including SNAP, Medicaid and subsidized housing. Because 58% of food system workers surveyed reported having no health care coverage, more than one-third of workers surveyed have used the emergency room for primary care, which taxpayers help cover. Finally, corporations like Walmart are able to determine wages and benefits for workers throughout their entire supply chain, given their massive procurement power and ability to dictate purchasing prices to its suppliers. This pressure and influence forces suppliers to lower their worker’s wages, drain trays for plants multiplying the number of workers robbed of fair and livable wages and taxpayer subsidization of corporate profits.

In short, when food system workers require public assistance, the onus rests on taxpayers and the federal government, rather than on those that are responsible for creating these unhealthy outcomes—corporations. After over thirty years of liberal trade policies beginning in the late 1970s and early 1980s, many developing countries have been left with a great dependence on the global market for basic food and grains. Developing countries had yearly agricultural trade surpluses of $1 billion in the early 1970s. Yet by 2000, the food deficit in such countries had grown to $11 billion per year. At the height of the 2007–2008 global food price crisis, Low-Income Food Deficit Countries import bills reached over $38 billion for basic cereal grains. Such systemic vulnerability is, in part, a result of international finance institutions, structural adjustment, free trade agreements, and a broader divestment of the state from agricultural development. Furthermore, not only are overproduction and US food aid to blame, but also corporate actors use such international crises as oppor-tunities to make additional calls for emergency aid coupled with further trade liberalization and increased investment in agricultural productivity. The Farm Bill in particular has been instrumental in establishing and maintaining such systemic vulnerability. For example, although the 2014 Farm Bill authorizes $80 million annually for the Local and Regional Procurement Program, which encourages greater use of food that is locally or regionally grown for food aid, it pales in comparison to the $1.75 billion Food for Peace Title II through which United States Agency for International Development provides food assistance. Furthermore, foreign economies are undermined not only by such efforts that directly shuttle surplus and heavily subsidized commodities—produced for the benefit of corporate entities—to developing countries, but also by production support programs themselves, such as commodity payments or crop insurance.

For example, a 2012 International Centre for Trade and Sustainable Development report found that the shift from direct payments to crop insurance support for farmers is likely to have far reaching effects on global trade and prices because of the anticipated change to cropping patterns. Specifically, the likelihood that the new programs will influence planting decisions is greatly enhanced because payments in all the new programs are calculated using actual planted acreage. Ultimately, if planting decisions are influenced enough, then program-induced changes in US crop acreage will be reflected in trade flows that have the potential to harm farmers in developing countries and cause fluctuations in global food prices. One major way corporations profit and exert their control with regard to education, research, and development is their influence over academic research and development. Agricultural research in the United States is carried out primarily by three entities: the federal government, largely through the US Department of Agriculture; academia, primarily through land-grant universities; and the private sector. Over the past several decades, corporate interests have co-opted publicly-oriented agricultural research and land-grant university research efforts in particular. The federal government created land-grant universities in 1862 by deeding tracts of land to every state to pursue agricultural research to support agricultural production in the United States. Although public investments have maintained agricultural research since the creation of these universities, over recent decades public funding has stalled, prompting land-grant universities to appeal to agribusiness to remedy such financial shortcomings. Significantly, the landmark 1980 Bayh-Dole Act pushed universities to take this particularly entrepreneurial role, generating revenue through producing patents from which the private sector could profit. The Bayh-Dole Act, as part of the neoliberalization of science and academic research itself, prompted greater industry influence over land-grant research, as university research agendas became oriented toward the needs of corporate partners.

Major agribusiness donors to land-grant universities across the United States, including Syngenta, Monsanto, PepsiCo, Nestle, Dow Agroscience, Chevron, DuPont and others, now push research carried out by faculty and students toward developments in bio-fuels, commodity crops research, genetically engineered foods, and other areas of interest. Land-grant universities today not only carry out corporate-directed research but also depend on agribusinesses to underwrite research grants, endow faculty chairs, sponsor departments, and finance the construction of new buildings. Even USDA research and USDA-funded research itself reflects corporate interests. The USDA spends roughly $2 billion per year on agricultural research, which goes toward funding USDA researchers and researchers at land-grant universities. This money, however, is largely directed toward a corporate-friendly industrial agriculture research agenda: the National Academy of Sciences found that USDA research prioritizes commodity crops, industrialized livestock production, technologies geared toward large-scale operations, and capital-intensive practices. The Farm Bill does not prioritize funding for more sustainable farming programs, with programs such as the Organic Agriculture Research and Education Initiative and Specialty Crop Research Initiative accounting for only 2% of the USDA’s research budget. Most research funding is directed toward commodity crops research. In 2010, for example, the USDA funded $204 million to research all varieties of fruits and vegetables, and spent $212 million to research just four commodity crops: corn, soybeans, wheat, and cotton. Another major way private industry continues to profit and exert their influence vis-à-vis relations of education, research, and development, is seed research and patents. Since the early 1980s, the global seed industry has grown substantially and is now worth an estimated $44 billion and is expected to grow to an estimated $85 billion by 2018. The cumulative effect of seed legislation has facilitated the massive consolidation of corporate power, thus securing corporate control of one of the most crucial agricultural inputs. This history of seed legislation began shortly before the New Deal, beginning with the US Plant Patent Act of 1930 and continued with the 1970 Plant Variety Protection Act. Significantly, seed legislation did not move into the judicial system until the 1980 Supreme Court decision Diamond v. Chakrabarty, which laid the legal groundwork for the privatization and commodification of the genetics of seeds. In 1985, Ex Parte Hibberd, an administration decision by the US Patent and Trademarks Office, extended property rights to the individual components of organisms, 4 x 8 grow tray including genetic information, thus anticipating some of today’s contentious Genetically Modified Organism debates. Ten years later, Asgrow Seed v. Winterboer denied the rights of farmers to save and resell patented seed products, marking the continuation of a series of legislation that progressively placed power in corporate hands. In 2001, J.E.M. AG Supply v. Pioneer Hi-Bred International, a legal dispute between a large seed company and small seed supply center, affirmed that newly developed plant breeds are covered by expansive utility patents. In 2013, furthermore, Bowman v. Monsanto held that patent “exhaustion doctrine” does not cover farmers’ reproduction of patented seeds through planting and harvesting without the patent owner’s permission, further reflecting and securing corporate profit and influence. Although inadequate disclosure laws make it difficult to determine the exact amount expended on the Farm Bill and on other pieces of legislation, during the two years preceding the passage of the Farm Bill on February 7, 2014, at least 600 companies spent over $500 million in lobbying. The largest spenders ranged from Fortune 500 leaders in banking, trade, transportation and energy to non-profit organizations. A joint investigation by Harvest Public Media and the Midwest Center for Investigative Reporting found that the top 18 corporations and groups spent at least $5 million each in total lobbying from 2012 to the First Quarter of 2014.

These corporations and groups include: the US Chamber of Commerce, Exxon Mobil, Du Pont, the American Bankers Association, Pharmaceutical Research and Manufacturers of America, Grocery Manufacturers Association, Wells Fargo, AARP, Monsanto, Independent Community Bankers of America, Coca-Cola, Association of American Railroads, Nestle, Nextera Energy, BNSF Railway Company, PMI Global Services Inc., Bayer Corporation, and American Forest & Paper Association. The commodities support programs outlined above make up one major set of Farm Bill issues influenced by such lobbying efforts. These direct payments have long received the attention of growers groups and other interest groups that are beholden to corporate interests. Specifically, alongside the Farm Bureau, the Farmers Union, and other general farm organizations, all major agricultural commodities are represented by a lobbying organization that aims to keep the Farm Bill’s commodity programs intact as per the supposed interest of the producers of such commodities. These organizations include: the National Cotton Council, the Sugar Association, and the National Corn Growers, among others. While indeed all industries are represented by lobbying organizations, the relative political and economic strength of actors within the US food system that are already oriented toward large-scale production, processing, distribution, and service—such as those above—highlights their significance, particularly concerning contemporary campaign finance reform efforts. With the change to crop insurance as the safety net centerpiece, banks and insurance companies spent at least $52.6 million in lobbying the 2014 Farm Bill and other issues in the two years prior to its passage. For example, Wells Fargo, the fourth-largest US bank, spent approximately $11.3 million in lobbying efforts, signaling the potential gain to be had by the company’s Rural Community Insurance Services, the largest crop insurance provider in the country. The American Bankers Association, another group that will benefit most from the boost to crop insurance, reported spending $14 million on lobbying, including advocacy for crop insurance and other rural lending plans. Other lobbyists for crop insurance included Independent Community Bankers of America, ACE INA Holdings and Zurich , the National Association of Professional Insurance Agents, and Deere & Co., the large equipment manufacturer that also has a crop insurance arm. Private sector spending on agricultural research has risen steeply since the 1970s and 1980s, exceeding public sector spending on agricultural research. From 1970 to 2006, private agricultural research expenditures—both in-house research and donations to land-grant universities—rose from $2.8 billion to over $8 billion, in inflation-adjusted 2014 dollars. Yet total public funding—directed toward land-grant universities and the USDA—rose from $3.1 billion to $6.1 billion in that same period. Federal funding of land-grant universities in particular reflect such trends: by the early 1990s, industry funding had already surpassed USDA funding of agricultural research at land-grant universities and by 2009, private sector funding had soared to $822 million, compared to $645 million from the USDA. Significantly, the economic recession substantially restricted research funding. Yet USDA land-grant university funding dropped twice as fast as private funding between 2009 and 2010, from 39.3% and 20.5%, respectively, reflecting the increasing dependence of university research on corporate funds, particularly during economic downturns. 

Stanley Hart White, Professor of Landscape Architecture at the University of Illinois Urbana-Champaign from 1922 to 1959, was granted US Patent 2,113,523 on 5th April 1938 for the Vegetation-Bearing Architectonic Structure and System in which he describes the method for creating an ‘architectonic structure of any buildable size, shape or height, whose visible or exposed surfaces may present a permanently growing covering of vegetation’. In six beautifully illustrated pages, Professor White reveals the new art of growing plants within/on a vertical, architectonic, substrate-holding frame, and in the process describes a new vertical garden type not fully realized till after his death in 1979. All that remains of White’s invention are his careful diaries, a series of patents, and his brother E. B. White’s correspondences about Stan’s new invention. Stanley Hart White is best known as an educator who modernized landscape pedagogy at the University of Illinois, influencing the work of Hideo Sasaki, Peter Walker, Richard Haag, and others, through his innovative teaching style and creativity. With the discovery of his patent for the first known green wall, or Botanical Bricks, he may also be credited as an inventor and technological innovator, conceptualizing the vertical garden and pioneering green modernism . White’s thoughts on vegetation-bearing architecture crystallize in his patent of 1938, 4×4 grow tray yet notions of a green wall emerge as early as 1931 in his lectures and writings on the modern garden.

Although the intended audiences for White’s early writings on vertical greenery are not yet apparent, the idea of a vegetation bearing garden enclosure preoccupies him for several years as documented in his personal journals, or Commonplace Books, in the University of Illinois Library Archives. Technical aspects of White’s green wall find their clearest articulation in US Patent 2,113,523, filed on 18th August 1937, yet the theoretical dimensions developed as a treatise on modernism and garden design, in which the vertical surfaces of the garden create a backdrop for modern living. In an essay titled ‘What is Modern’, White discusses the green wall as a design solution for the modern garden, allowing for the preservation of a free plan and composition of a garden in the vertical dimension. His references to Walter Gropius, Le Corbusier, Frank Lloyd Wright, Louis Sullivan, Walt Whitman, Charlie Chaplin, Norman Bel Geddes, Adolph Appia, Sheldon Cheney, Walt Disney, and others, situates the work among a group of ‘moderns’ concerned with changing lives through art and architecture.6 The Vegetation-Bearing Architectonic Structure and System evolved as a response to the problem of modernism in garden design, and is a unique contribution of landscape architecture to this effort, representing a clear translation of garden theory into garden form and legalese. The prescience of this work is astounding, predicting not only the emergence of the vertical garden in the contemporary built environment, but a method of scholarship in patent development not widely accepted by US universities until the 1970s. White’s inchoate drawings and description of a green wall in 1931–32 mature until his application for the Vegetation-Bearing Architectonic Structure and System on 18th August 1937, where he artfully translates garden theory into United States Patent and Trademark Office legalese with the help of his attorney, Elmer Hovenden Gates of Arlington, Virginia.

The new art of vegetation bearing architecture was entirely novel at the time of application, and no citations of prior art are associated with White’s invention. Currently, thirty four international patents cite US Patent 2,113,523 as prior art, encoding an array of inventions from grass cube chairs, to vegetation-bearing gabion walls. Interestingly, White’s lawyer, Elmer Hovenden Gates, and proposed business partner, William M. McPherson, patented related vegetation-bearing technologies within weeks of his submission. More than 50 patents cite the Vegetation Bearing Cellular Structure and System, Vegetation-Bearing Display Surface, and the Vegetation-Bearing Architectonic Structure and System, collectively encoding a diverse ensemble of environmental technologies. The legalese defining this new field offers valuable insights into the founding principles of vegetation-bearing architecture as a chimera of architectonic structure and vegetated system. According to White, architectonics relates to ‘the art of landscaping structure as well as to buildings, but distinguished from the art of plant culture’. Within this architectonic structure, plant growth is supported through a layering of horticultural substrates and reticular materials. In this configuration, the ‘vegetation in its final positions has its roots within the compost while the tops of the vegetation would extend through the reticular surfaces of the units or compounds into the open air where their normal development occurs’. The patents legalese describes not only the technical specifications of White’s new invention, but also the proposed scope of vegetation-bearing architecture as a new art. This scope is of particular interest with the emergence of the vertical garden and green wall in the contemporary built environment, as the language that defines the new art also encodes innovations in related technologies today.

Specifically, corporate control refers to control of political and economic systems by corporations in order to influence trade regulations, tax rates, and wealth distribution, among other measures, and to produce favorable environments for further corporate growth. Structural racialization refers to the set of practices, cultural norms, and institutional arrangements that are reflective of, and help to create and maintain, racialized outcomes in society, with communities of color faring worse than others in most situations. In this light, the production of racial/ethnic, gender, and economic inequity in the United States is more so a product of cumulative and structural forces than of individual actions or malicious intent on behalf of private or public actors. In order to challenge and eliminate corporate control and structural racialization in the United States, therefore, it is necessary to analyze the ways that public and private institutions are structured. It is also necessary to analyze how government programs are administered and operate in ways that reproduce outcomes that marginalize low-income communities, women, and communities of color in terms of health, wealth, land access, power, and degree of democratic influence. Additionally, as this report aims to do, it is crucial to analyze the genesis and formation of critical institutions and structures themselves. Therefore, the US Farm Bill—the flagship piece of food and agricultural legislation since its inception in 1933, which informs the heart of public and private policies that make up much of the US food system—is the subject of this report. This report is of particular importance now for two reasons. First, the Farm Bill will be under consideration again in 2019, yet there is no comprehensive critique of the Farm Bill that addresses its underlying contradictions, particularly with regard to racial/ethnic, gender, and economic inequity. Second, it is imperative that campaigns by grassroots, community, and advocacy organizations—generally most active during the period of Farm Bill negotiations in Congress—have enough time to gather adequate information and conduct in-depth analysis for targeted yet comprehensive policy change. As such, the timing of this report is also imperative for coalition-building efforts and the growth of an effective broad-based food sovereignty movement.Corporate consolidation and control have become central features of the US food system, and of the Farm Bill in particular. As of 2014, large-scale family-owned and non-family-owned operations account for 49.7% of the total value of production despite making up only 4.7% of all US farms. As of 2013, only 12 companies now account for almost 53% of ethanol production capacity and own 38% of all ethanol production plants. As of 2007, four corporations own 85% of the soybean processing industry, 82% of the beef packing industry, 63% of the pork packing industry, and manufacture about 50% of the milk. Only four corporations control 53% of US grocery retail, and roughly 500 companies control 70% of food choice globally. At every level of the food chain, from food production to food service, workers of color typically earn less than white workers. For example, a majority of farm workers who receive “piecerate” earnings , and many of whom are migrants from Mexico, frequently earn far less than minimum wage—an exploitative practice deeply tied to immigration policy, as elaborated upon below. On average, white food workers earn $25,024 a year while workers of color make $19,349 a year, greenhouse racking with women of color, in particular, suffering the most. Furthermore, few people of color hold management positions in the food system, while white people hold almost three out of every four managerial positions. One result of this racial disparity in food system labor is that non-white workers experience a far greater degree of food insecurity than their white counterparts.Food insecurity in the US disproportionately affects low-income communities and communities of color, and these communities are over represented in the lowest-paying sectors of the labor market.

For example, as of 2013, 14.3% of US households—17.5 million households, roughly 50 million persons—were food insecure. The report also found that the rates of food insecurity were substantially higher than the national average among Black and Latino/a households, households with incomes near or below the federal poverty line, and single parent households. Racial/ethnic inequity with regard to land access is a defining feature not only of the corporate-controlled food system, but also of the US government itself, which, even years after emancipation, has made it nearly impossible for Blacks and other communities of color to acquire and keep land in substantial numbers. For example, in 1920, 926,000 US farmers were Black and they owned over 16 million acres of land, and by 1997, fewer than 20,000 US farmers were Black and owned approximately 2 million acres of land. While white farmers were losing their farms during these decades as well, the rate that Black farmers lost their land has been estimated at more than twice the rate of white-owned farm loss.Though the Farm Bill itself does not deal directly with immigration, the impact of the Bill on farmworkers cannot go unnoticed. The combination of an immigration system easily exploited by employers, and workers’ low income, limited formal education, limited command of the English language, and undocumented status, greatly hinders farmworkers from seeking any retribution or recognition of their rights. With limited legal aid, many agricultural workers fear that challenging the illegal and unfair practices of their employers will result in further abuses, jobs losses, and, ultimately, deportation. Given the fact that the Farm Bill supports many of those companies that employ farmworkers, connections must be drawn to highlight how the Farm Bill upholds and perpetuates structural injustice among farmworkers. In the US, exposures to environmental hazards have disproportionately impacted low-income communities and communities of color. As a major contributor to global climate change and the racialized distribution of its impacts, conventional agricultural production practices, in particular, have been instrumental in maintaining and upholding these disparities. Furthermore, low-income communities and communities of color in the United States bear the burden of the impacts caused by climate change. For example, these populations breathe more polluted air than other Americans, suffer more during extreme weather events, have fewer means to escape such extreme weather events, and disproportionately experience greater hardship due to rising energy, food, and water costs.This report found a number of structural barriers to addressing these racial/ethnic, gender, and economic inequities. First, the Farm Bill itself is increasingly imbricated in, and ultimately functions as a pillar of, neoliberalism. The long term shift from the subsidization of production and consumption to the subsidization of agribusiness has structurally positioned low-income communities and communities of color on the losing side of such shifts. This population has also been given fewer options for recourse, given the ways in which the Farm Bill has been designed to be insulated from democratic influence, particularly by way of countless layers of congressional committees. Second, under the current Farm Bill, supporting public nutrition assistance programs and fighting poverty and racial/ethnic inequality, are antithetical to one another, despite the evidence that suggests otherwise. Specifically, while such public assistance programs do provide support to some of the most marginalized communities, they ultimately maintain structural inequity, particularly in terms of wealth, by channeling profits to corporations such as Walmart and other large retailers, which benefit greatly from distributing benefits such as SNAP. Many of these corporations are then able to funnel profits back to their corporate headquarters outside their respective retail sites, while still paying workers low wages and granting few benefits at every level of the food system. Finally, this report found that supporting the inclusion of producers of color into current payment schemes, and fighting poverty and racial/ethnic [ii] Neoliberalism is a new period of capitalism, particularly since 1970s and 1980s, characterized by unparalleled global reach of economic liberalization, open markets, free trade, and deregulation.

Again, Wolf and Sumner find no evidence of a bimodal dairy industry using Farm Cost and Return Surveys of dairy farms for the years 1989 and 1993. In MacDonald et al. , they suggest that larger dairies tend to have lower costs per cow, which allows them to capture greater economies of scale. The cost-minimizing efforts of individual dairy farms will influence the specific farm management choices that the farm makes, as only the individual farm has a true sense of where it sits on its long-run average cost curve. Some of these management decisions include the dairy’s strategy to capture economies of scope, through sales diversification, or vertically integrate to minimize input and production costs. Sumner and Wolf find that vertical integration has little influence on the farm size and that the tendency for farms in the Pacific and South to have larger herd sizes remains true, even when accounting for the levels of vertical integration. The farm’s choice to incorporate different management strategies reflects the incentives and constraints that the farm faces, i.e., influences of geographic location and capital. Other influences on management choices by dairies are in part due to different environmental regulations in each state that impact the average cost of production for dairy farms. There has been a significant amount of agricultural economic research on dairy farm size with respect to their risk management and technical efficiency. Tauer finds that smaller dairies in New York do have a high average cost of production than dairies with larger herd sizes, grow trays but that these higher costs are due to inefficiencies and efficient small dairies are competitive with the larger dairies. Tauer and Mishra examine whether differences in technology or efficiency characterize the higher cost that smaller dairy farms face and find that using a frontier cost of production analysis show that inefficiencies in smaller dairies characterize the higher costs, not technological differences.

There has also been significant analysis in farm structure changes of the dairy industry. Zimmermann and Heckelei utilize a Markov Chain Model on dairies in the European Union to characterize farm size change and find that regional characteristics such as off-farm opportunities and unemployment rates are significant in relation to dairy farm size change. They also find that high milk prices slow down farm size change due to high milk prices correlation to uncertainty and price volatility leading to a decrease in investment. Wolf details how dairy farms in Michigan have increased their use of risk management tools from 1999 to 2011 and find that the use of such risk management tools was positively correlated with measures of dairy farm size. This research also discusses how age related to risk management adoption with younger dairy farmers being less likely to utilize the risk management tools. Wolf outlines characteristics of dairy farm size change across time Beyond management decisions influencing or being correlated with the farm size and farms’ decision to exit, previous economic literature has hypothesized about the possible influences of operator characteristics, like human capital , the number of female operators, the age of operators, or other farm operator characteristics on farm size. Sumner and Leiby find that human capital positively influences the size of the farm, and this is hypothesized to be due to increasing opportunity costs for dairy farmers with high levels of human capital. Dairy farmers that have the possibility of making more money elsewhere will do so, therefore it seems likely that dairy farms with sufficient returns, which tend to be found on larger dairy farms, will attract high human capital management. Another aspect of the previous research related to farm size and the dairy industry is farm exits. There have been several studies of individual farm movement across farm size groups and characterization of exits.

Most of this literature, however, has been limited to regions or states. Macdonald et al. finds that in 2016 about 40 percent of dairy farms with at least 2,000 milk cows did not have positive net returns and that the share of dairies that did not have positive net returns increased as herd size decreased. However, they do note that negative returns in the dairy industry are seen as temporary lows by dairy operators, so they do not serve as a direct indication of an expected exit from the industry. Other reasons for exits from agriculture, or dairy specifically, include increased suburbanization of previously agricultural land, driving land prices up, and strong local economies, opening off-farm employment opportunities for farm operators. As outlined in Sumner and Leiby and Sumner , the human capital element remains prevalent through economic explanations of farm exit. Of course, age of the farm operators plays key role. Macdonald et al. discuss the role of the advanced age of many dairy farmers and the fact that many dairy farms are family-run, suggesting that there will be an increase in exits as more farmers choose to retire. Furthermore, the study relates the probability of exit to farm size, finding that not only does the age of the operator increase the likelihood of exit, but the smaller the farm size also increases the probability of exit. This section discusses the sample used in this analysis and details changes in the COA questions that are relevant to this analysis. The research utilizes COA data from 2002, 2007, 2012, and 2017 for six select states: California, Idaho, New Mexico, New York, Texas, and Wisconsin. The results presented have gone through a disclosure review process and no data on individual/farm-specific is specific to individual farms and instead characterizes them more generally. Although the COA is federally mandated, it does not collect data on every U.S. farm and as such weights responses to create the most accurate sample that reflects the true U.S. farm sample. As discussed in Chapter 2, I use a specific definition of a commercial dairy in order to capture dairies with significant engagement with the dairy industry.

A commercial dairy for the purposes of this analysis is defined as a farm with at least 20 milk cows on the farm as of December 31 of the Census year and the farm must have dairy or milk sales revenue above the dollars of milk sale revenue that would have been generated by 30 milk cows. The survey questions asked of farmers and ranchers by the COA change slightly every Census round, although most remain the same across time. Below are descriptions of question changes for relevant variables to the analysis. First, in 2002 and 2007, farms were asked for the total amount of dairy sales in that year, but in 2012 and 2017, this question was dropped and replaced with the total amount of milk sales. Furthermore, whether the dairy farm had any level of organic production was only asked in 2007, 2012, and 2017. Second, operator characteristic questions have become more detailed over the years and allowed more information about operators to be collected. In 2002, 2007, and 2012, the COA asked detailed operator characteristic questions about up to three operators, but only one operator was identified as the principal operator. In 2017, the COA expanded its detailed operator questions to include up to four operators and allowed for up to four operators to be identified as principal operators. In this Chapter, pruning cannabis the operators for which the number per farm is limited and detailed information is provided will be referred to as the “core operators.” There is other no limit to the number other operators listed per farm and only the gender of each such operator and the total number per farm are provided in the Census. The COA has three potentially relevant farm size variables for dairy farms, the number of milk cows, the value of farm production, and the value of milk or dairy sales. I utilize all three in this chapter. However, I focus particular attention on the number of milk cows for the kernel density graphs. I characterize the distributions of number of milk cows per commercial dairy farm using two approaches. One approach is to fit a non-parametric distribution by year, and by state for each year to the data on milk cow herd size per farm. The other approach is to fit two commonly used parametric distributions to characterize dairy farm size distributions for the national and individual states over census years. One aim of my thesis is to characterize the farm size distribution of dairy farms and fitting parametric density functions serves as a starting point for characterizing and analyzing dairy size distribution. As explained above, there is previous literature that utilizes parametric distributions to characterize farm size and this research provides evidence that commonly used distributions do not fit well with the U.S. commercial dairy industry. It is common in farm size analysis to fit parametric density functions to characterize farm size distribution . I create kernel density plots for the herd size distribution by state across the years and then find and fit two common parametric density functions to the distribution.

This section will be structures as follows: a brief overview of the mathematics used in fitting parametric density functions. There are three steps to fitting the parametric density function to the farm size variables. First, I hypothesize based on the kernel density plots what distributions seem reasonable. For this analysis I use the lognormal and the exponential function, as those are two common distributions used in farm size literature and are likely shapes for most farm size distributions. Lognormal is the typical selection, as it is referenced in Gibrat’s Law. The exponential distribution was selected because it can account for the same skewed shape but has more flexibility. Second, I estimate the parameters of interest needed to form that distribution in order to create an estimated distribution of random numbers that follow the specific distribution. For this analysis, the measures of farm size, the number of milk cows for each farm, are random variables x1, x2, x3, …, xn, where n is the sample size of farms, for which the joint distribution depends on distribution parameters. For example, using the lognormal the parameters are the mean and variance, and there are two related parameters for the exponential distribution. From there, we can calculate the estimates of these parameters to create a different distribution with those same parameters and compare them to the actual distribution of the number of milk cows. Some estimated parametric distributions appear to have slight irregularities, this is due to the number of observations and the impose parameters. This section will summarize the resulting farm size graphs and detail the trends across time and states. Overall, when looking at the six select states together commercial dairy farm distributions have shifted towards larger dairies. In 2002, there was a clear peak in the number of farms with less than 200 milk cows, but the peak falls significantly from 2002 to 2017 . Whereas farm size distribution shows a clear increase in the farms with larger herd sizes in 2017. Although this graph gives interesting detail about the trends in herd size for the U.S. overall it is mostly characterized by Wisconsin and New York which have a significantly larger share of the number of commercial dairies and tend to have smaller herd sizes relative to other states. This graph clearly shows that there remains a large share of dairies that have a herd size of less than 200 milk cows, despite the relative shift in herd size. Moving to state-specific trends, overall California dairies have had larger herd sizes than other states, such as New York or Wisconsin across all years . California had a peak in the share of dairies with less than 1,000 milk cows from 2002 to 2017, but the peak fell significantly between 2007 and 2012. There was a clear shift in 2012 with an increase in the 1,000 to 2,000 milk cow herd size in 2012 and then another shift in 2017 in the 2,000 to 3,000 milk cow herd size. This documents a clear movement of California dairies towards larger herd sizes and a decrease in smaller herd sizes. Idaho had a large peak in commercial dairies with less than 500 milk cows in 2002 and then a significant drop in that peak in 2007 with smaller subsequent decreases in 2012 and 2017 .

In another example, several of the farmers learned about variations in their soil type by directly observing how soil “behaved” using cover crop growth patterns. These farmers discussed that they learned about patchy locations in their fields, including issues with drainage, prior management history, soil type, and other field characteristics, through observation of cover crop growth in their fields. Repeated observations over space and time helped to transform disparate observations into formalized knowledge. As observations accumulated over space and time, they informed knowledge formation across scales, from specific features of farmers’ fields to larger ecological patterns and phenomena. More broadly, using cover crop growth patterns to assess soil health and productivity allowed several farmers to make key decisions that influenced the long-term resilience of their farm operation . This specific adaptive management technique was developed independently by several farmers over the course of a decade of farming through longterm observation and experimentation – and, at the time, was not codified in mainstream farming guidebooks, policy recommendations, or the scientific literature . For these farmers, growing a cover crop on new land or land with challenging soils is now formally part of their farm management program and central to their soil management. While some of the farmers considered this process “trial and error,” in actuality, all farmers in this study engaged in a structured, iterative process of robust decision-making in the face of constant uncertainty, similar to the process of adaptative management in the natural resource literature . This critical link between farmer knowledge formation and adaptive mangement is important to consider in the broader context of resilience thinking, cannabis drying trays wherein adaptive management is a tool in the face of shifting climate and changing landscape regimes .

The underlying social and ecological mechanisms for farmer knowledge formation discussed here may have a role in informing adaptive management and pathways toward more resilient agriculture . In this sense, farmer knowledge represents an overlooked source for informing innovation in farming alternatively. Farmer knowledge provides an extension to scientific and policy knowledge bases, in that farmers develop new dimensions of knowledge and alternative ways of thinking about aspects of farming previously unexplored in the scientific literature. Farmers offer a key source of and process for making abstract knowledge more concrete and better grounded in practice, which is at the heart of agriculture that is resilient to increased planetary uncertainties .Most of the farmers considered themselves separate from scientific knowledge production and though scientific knowledge did at times inform their own knowledge production, they still ultimately relied on their own direct observation and personal experiences to inform their knowledge base and make decisions. This finding underscores the importance of embedding theory in practice in alternative agriculture. Without grounding theoretical scientific findings or policy recommendations in practice, whether that be day-to-day practices or long-term management applied, farmers cannot readily incorporate such “outsider” knowledge into their farm operations. Farmers in alternative agriculture thus may provide an important node in the research and policymaking process, whereby they assess if scientific findings or policy recommendations may or may not apply to their specific farming context – through direct observation, personal experience, and experimentation.Similar to Sūmane et al. , we found that the process for farmer knowledge formation, or precisely how farmers learn, is systematic and iterative in approach. In this study, farmer ecological knowledge was developed over time based on continuous systematic observation, personal experiences, and/or experimentation.

This systematic approach that relies on iterative feedback to learning applied among these organic farmers is akin in approach to examples of adaptive management in agriculture . As highlighted in the results, it is possible for a farmer to acquire expert knowledge even as a first- or second-generation farmer. Documenting this farmer knowledge within the scientific literature – specifically farmer knowledge in the context of relatively new alternative farmers in the US – represents a key way forward for widening agricultural knowledge both in theory and in practice . This study provides one example for documenting this farmer knowledge in a particularly unique site for alternative agriculture. Future studies may expand on this approach in order to document other sites with recent but practical agricultural knowledge on alternative farms.Farmers in this study tended to think holistically about their farm management. For example, when the farmers were asked to talk about soil management specifically, several of the farmers struggled with this format of question, because they expressed that they do not necessarily think about soil management specifically but tend to manage for multiple aspects of their farm ecosystem simultaneously. This result aligns with similar findings from Sūmane et al. across a case study of 10 different farming contexts in Europe, and suggests that farmers tend to have a bird’s eye view of their farming systems. Such an approach allows farmers to make connections across diverse and disparate elements of their farm operation and integrate these connections to both widen and deepen their ecological knowledge base.For most farmers in this study, maintaining ideal soil structure was the foundation for healthy soil. The farmers emphasized that ideal soil structure was delicately maintained by only working ground at appropriate windows of soil moistures. Determining this window of ideal soil moisture represented a learned skill that each individual farmer developed through an iterative learning process.

This knowledge making process was informed by both social mechanisms gained through inherited wisdom and informal conversations and ecological mechanisms through direct observation, personal experiences, and experimentation .As these farmers developed their ecological knowledge of the appropriate windows of soil moisture, their values around soil management often shifted. In this way, over time , farmers in this study learned that no amount of nutrient addition, reduced tillage, cover cropping, or other inputs, could make up for damaged soil structure. Destroying soil structure was relatively easy but had lasting consequences and often took years, in some cases even a decade, to rebuild. This key soil health practice voiced by a majority of farmers interviewed was distinct from messaging about soil health vis-a-vis extension institutions, heavy duty propagation trays where soil health principles focus on keeping ground covered, minimizing soil disturbance, maximizing plant diversity, keeping live roots in the soil, and integrating livestock for holistic management . While these five key principles of soil health were mentioned by farmers and were deemed significant, for most farmers interviewed in this study, the foundation and starting point for good soil health was maintaining appropriate soil structure. The results of this study emphasize that the most successful entry point for engaging farmers around soil health is context specific, informed directly by local knowledge. Among farmers in Yolo County – a significant geographical node of the organic farming movement – soil structure is a prevalent concept; however, in another farming context, this entry point may significantly diverge for social, ecological, economic, or other reasons. Each farming context therefore necessitates careful inquiry and direct conversation with local farmers to determine this entry point for engagement on soil health. For this reason, in some cases it may be more relevant to tailor soil health outreach to the local context rather than applying a one-size-fits all model.The capacity to learn and pass on that learning are essential for farms that practice alternative agriculture to be able to adapt to ever changing social and ecological changes ahead . Across all farmers interviewed, including both first and second-generation farmers, farmers stressed the steep learning curves associated with learning to farm alternatively and/or organically. While these farmers represent a case study for building a successful, organic farm within one generations, the results of this study beg the question: What advancements in farm management and soil management could be possible with multiple generations of farmer knowledge transfer on the same land? Rather than re-learning the ins and outs of farming every generation or two, as new farmers arrive on new land, farmers could have the opportunity to build on existing knowledge from a direct line of farmers before them, and in this way, potentially contribute to breakthroughs in alternative farming. In this sense, moving forward, agriculture in the US has a lot to learn from agroecological farming approaches with a deep multi-generational history . To this end, in most interviews – particularly among older farmers – there was a deep concern over the future of their farm operation beyond their lifetime.

Many farmers lamented that no family or individual is slated to take over their farm operation and that all the knowledge they had accumulated would not pass on; there exists a need to fill this gap in knowledge transfer between shifting generations of farmers, safeguard farmer knowledge, and promote adaptations in alternative agriculture into the future. As Calo and others point out, technical knowledge dissemination alone will not resolve this ongoing challenge of farm succession, as larger structural barriers are also at play – most notably, related to land access, transfer, and tenure .Most studies often speak to the scalability of approach or generalizability of the information presented. While aspects of this study are generalizable particularly to similar farming systems, the farmer knowledge presented in this study may or may not be generalizable or scalable to other regions in the US. To access farmer knowledge, relationship building with individual farmers leading up to interviews as well as the in-depth interviews themselves required considerable time and effort. While surveys often provide a way to overcome time and budget constraints to learn about farmer knowledge, this study suggests that to achieve specificity and depth in analysis of farmer knowledge requires an interactive approach that includes – at a minimum – relationship building, multiple field visits, and in-depth, multi-hour interviews. Accessing farmer knowledge necessitates locally interactive research; this knowledge may or may not be immediately generalizable or scalable without further locally interactive assessment in other farming regions.One of the best ways to plan a garden is to make a map of the proposed area using grid paper and drawing it to scale. Look up the space requirements for the vegetables you’re interested in; consult your local UCCE Farm Advisor or Master Gardener and the publications listed in “For More Information” for advice on this subject. Draw the vegetables in appropriate places on the map. Also include planting dates—this will help you remember when and where to plant different crops. Vegetables need a steady supply of water during growth, so make certain there is an adequate and handy water source near the site. A level garden is necessary for uniform watering, but if the ground slopes, contour planting and drip irrigation allow water to be distributed evenly. Choose a site with rich, fertile soil that is free of weeds, rocks, and debris. Avoid shallow or compacted soils. If your soil is less than ideal, you may need to amend it or plant in raised beds .Full sunlight—a minimum of 6 to 8 hours per day—is necessary for some crops that produce “fruit,” such as tomatoes and corn. Full sun is ideal for all vegetables, but root and leafy crops can tolerate some shade. Look for shadows that may be cast over the planted area; note how much of the garden would be in shade and for how long each day. Keep in mind that shadow patterns change with the seasons. If possible, avoid planting under trees or on the north side of tall buildings. If tall and short plants are to be planted closely together, put the tall ones on the north side so the tall plants don’t cast shade on shorter plants next to them.Soil should be spaded or rototilled when it is moist but not wet. A good time to do this is in autumn before rain begins; it can be done again in spring if necessary. Work the soil about 6 to 10 inches deep, but avoid bringing subsoil to the surface. While working the soil, add preplant fertilizer . Rake the turned seedbed in several directions while it is still soft and full of moisture, so that any large clods or layered soils are broken up. The soil should have a uniform texture to a depth of 6 to 10 inches .

The number of certified operations and cropland acreage in California doubled between 2002 and 2016. State organic crop sales increased almost tenfold at the farm level, in real terms, during the same time period . This essay uses field-level pesticide application records and a fixed-effects model to analyze changes in the environmental impacts of pesticide use for both organic and conventional fields over 21 years. The database covers all registered agricultural pesticide applications in California, and contains over 48 million pesticide application records for over 64,000 growers and 781,000 fields from 1995 to 2015. In total, data from more than 55,000 organic fields and 11,000 growers who operated organic fields are analyzed in this essay. The Pesticide Use Risk Evaluation model is used to assess the environmental impacts of pesticide use . The results show that the environmental impact of pesticide use per acre is lower in organic fields across all of the environmental dimensions for which PURE indexes are defined: surface water, groundwater, soil, air, and pollinators. The difference in the impact on air is the smallest because natural pesticides are not systematically different from synthetic pesticides in terms of volatile organic compound emissions. The estimated impacts on all five environmental dimensions are positively correlated with farm acreage. The measure of farmer experience is positively correlated with estimated impacts per acre on surface water and groundwater, hydroponic drain table and negatively correlated with estimated impacts on soil, air, and pollinators but the difference associated with variation experience are smaller than the estimated effect of whether the field is organic or not by orders of magnitude. Environmental impacts and the difference between organic and conventional production vary by crop.

Four major California crops, lettuce, strawberries, processing tomatoes, and wine grapes, are examined in detail.The benefit from organic agriculture is partially paid by consumers through a price premium for organic products . Whether organic production is the most cost effective way to reduce the environmental impacts of agriculture is not the focus of this essay. However, readers can gain some insight into the performance of organic agriculture by comparing the cost of alternative tools and their effects on environmental quality. The contribution of this essay is threefold. First, it links the environmental impacts of organic crop production directly to pesticide applications. To the best of my knowledge, no other studies have examined this relationship. Previous literature provided abundant evidence on the environmental impact of organic agriculture as a system but failed to quantify the impact of specific farming practices . Here, AIs and their contributions to environmental impacts are identified individually, which enhances the understanding of the differences in pesticide use between organic and conventional agriculture and how they vary across crops. Second, this essay uses the PURE model to assess the environmental impacts of pesticide use . Compared to the risk quotient approach, which is another common method in the literature , the PURE model provides a more salient measure of environmental impacts by incorporating additional environmental information, such as the distance from the pesticide application to the nearest surface water. The PURE model calculates risk indices for five environmental dimensions: surface water, groundwater, soil, air, and pollinators. Third, by using the Pesticide Use Report database, this essay’s findings are based on the population of pesticide application data.

Prior works include meta-analyses that cover numerous field experiments and commercial operations examined for a crop or a small geographic area over a limited period of time. California’s agriculture is characterized by many crops and diverse climate and soil conditions. The comprehensive coverage of the PUR database eliminates any sample selection issue. The rest of the essay is organized as follows: section 2 introduces the PUR database and PURE model and presents summary statistics of historical pesticide use, section 3 provides the identification strategy to tackle grower heterogeneity, section 4 presents industry level and crop-specific estimation results, and section 5 concludes. To obtain the USDA organic certification, growers must meet requirements on several aspects of production: pesticide use, fertilizer use, and seed treatment. The requirement on pesticide use is burdensome because pesticides approved in organic agriculture are expensive and have less efficacy. Pesticide and fertilizer AIs used in organic agriculture undergo a sunset review by the National Organic Standards Board every five years and the main criterion is whether the ingredient is synthetic or not. In general, it is not reasonable for growers to use those pesticides exclusively but not apply for the organic certification, given higher price and lower efficacy of those pesticides. Therefore, growers who comply with the NOP’s requirement on pesticide use can be viewed as equivalent to certified organic growers for the data sorting purpose. In Wei et al. , authors located individual organic fields using this approach. Namely, any field without a prohibited pesticide applied for the past three years is considered organic. Their paper compared organic crop acreage from PUR to other data sources and showed that pesticide use records alone can be used to identify organic crop production. Environmental conditions for each field and toxicity values for each chemical are used to calculate the value of the PURE index developed by Zhan and Zhang .

The PURE index has been used in previous studies to represent environmental impacts of pesticide use . The PURE index indexes environmental impacts of pesticide use in five dimensions: surface water, groundwater, soil, air, and pollinators. For each dimension, the PURE index is calculated on a per acre basis and it varies from 0 to 100, where 0 indicates trivial impact and 100 rep- resents the maximum impact. Excluding air, the PURE index is the ratio of the predicted environmental concentration to toxicity to the end organisms. The PEC estimates the effect of the pesticide application on the concentration level for chemicals in the environmental sample. The toxicity values cover both acute measures, such as LD50, and long-term measures, such as No Observed Effect Concentration and acceptable daily intake for humans. End organisms are fish, algae, and water fleas for surface water, humans for groundwater, earthworms for soil, and honeybees for pollinators. The PURE index for air is calculated based on potential VOC emissions, which is a common measure of airborne pollutants emitted from agriculture production . The emission of VOCs is defined as the percentage of mass loss of the pesticide sample when heated. Unlike toxicity, VOC emissions do not have a strong link to whether the AIs are synthetic or natural. For example, the herbicide Roundup®, which contains glyphosate, has zero VOC emissions because there is no evaporation or sublimation. Meanwhile, sulfur products, which are widely used in organic agriculture, also have zero VOC emissions. Inert ingredients, which are not covered in this essay, are also found to have negative impacts on the environment and on pollinators in particular . Conventional and organic growers adopt different pest management practices. As specified by the NOP, organic growers shall use pesticides only when biological, cultural, and mechanical/physical practices are insufficient. Chemical options remain essential for organic pest management programs. Currently over 7,500 pesticide products are allowed for use in organic crop and livestock production, processing, and handling. In Figure 1.1, the acreage treated with different types of pesticides is shown on the left y-axis for both conventional and organic fields. Treated acreage is divided evenly among types for AIs that belong to multiple pesticide types, such as sulfur, which is both a fungicide and an insecticide. The average number of pesticide applications per acre, which is defined as the total treated acreage divided by the total planted acreage, is plotted against the right y-axis in both panels. This is a common measure of pesticide uses that controls for differences in application rate among pesticide products . If multiple AIs are used in a single application, rolling benches hydroponics the treated acreage is counted separately for each AI. Planted acreage remained stable for conventional agriculture over the study period, so changes in the average number of applications per acre were due to changes in treated acreage. Organic planted acreage grew dramatically, but treated acreage increased even more. The number of applications per organic acre rose from 2 to 7. Figure 1.1 provides a highly aggregated view of pesticide use as different pesticide products with different AIs and application rates are used in conventional and organic fields. Examining the Figure 1.1 , insecticide is the most used pesticide type, accounting for 36% and 44% of total treated acreage in conventional and organic agriculture respectively in 2015. Herbicide is the second most used type of pesticide in conventional fields. In contrast, organic growers’ use of herbicides is limited. Fungicide is another major pesticide type, and sulfur is the most used fungicide AI in both conventional and organic fields.

Sulfur is an important plant nutrient, fungicide, and acaricide in agriculture. The pesticide group “others” primarily includes plant growth regulators and pheromones. Disaggregating insecticide use provides more detailed insight into the nature of the difference between conventional and organic production. Figure 1.2 plots the insecticide treated acreage by physiological functions affected . Only three groups of insecticides are available to organic growers, while six are available to conventional growers. In conventional agriculture, 67% of treated acreage in 2015 was treated with insecticides that targeted nerves or muscles, which include organophosphates, pyrethroids, and neonicotinoids. For organic growers, two AIs, spinosad and pyrethrins, are available to target those physiological functions. The “unknown” category, which is mostly sulfur, accounted for a significant portion of treated acreage in organic agriculture. Insecticides that target the midgut, which includes Bacillus thuringiensis and several granulosis viruses, are widely applied in organic fields. Conventional growers rarely use them due to the high cost. In 2015, acreage treated with midgut targeted insecticides was 1% of total treated acreage in conventional agriculture and 24% in organic agriculture. A detailed discussion of insecticide and fungicide use by mode of action in conventional and organic production is in the appendix. Insecticides and fungicides in the two pest management programs have different modes of action and pose different levels of environmental impact. Simply comparing treated acreage or the amount of pesticide products used does not identify the differences in environmental impacts. In this context, the PURE index serves as a consistent measure across farming systems.Figure 1.3 plots PURE indices for conventional and organic fields by year. Index values for air and soil are significantly higher than those for the other environmental dimensions in both farming systems, which means that pesticide use in general has greater impacts on air and soil quality than groundwater, pollinators, and surface water. Risk indices of conventional fields are relatively stable from 1995 to 2015, with no obvious overall changes for air or soil, despite the many changes that have occurred during this 20-year period in regulations and grower portfolios. While PURE indices decreased 16% for surface water, 26% for pollinators, and 7% for groundwater over the same time period, these three were much less impacted by pesticides in 1995, the beginning of the study period. Despite the numerous regulatory actions designed to reduce environmental impacts over this 20-year period, such as the methyl bromide phase-out, large-scale substitution of pyrethroids for organophosphates, and regulations to reduce VOC emissions from non-fumigant products, the overall environmental impacts of conventional pesticide use show only limited reductions when aggregated across all crops. PURE indices for organic fields are similar to conventional fields in that the air and soil have significantly higher index vales than the others. However, the aggregate risk indices in all five dimensions are much lower in organic fields. Compared to conventional agriculture, organic agriculture has dramatically lower PURE indices for surface water , groundwater , air , soil , and pollinators . The reduction for air varies greatly across major California crops. Large reductions in the PURE index for air are observed for table grapes , wine grapes , and processing tomatoes , while others had relatively small ones such as leaf lettuce and almonds . The reduction in the PURE index for soil varies across crops as well, ranging from leaf lettuce to carrots . For surface water, groundwater, and pollinators, the differences between the PURE index in organic and conventional fields are similar across crops.

The present study found no effect of adolescent cannabinoid exposure in the escalation model, suggesting that adolescent WIN exposure may not facilitate the acquisition, maintenance, or escalation of cocaine use in adulthood. An alternative hypothesis is that the effect of cannabinoid use may not be observed on cocaine intake per se; instead, cannabinoid exposure may produce an increase in the motivation for cocaine, leading to an increase in compulsive cocaine seeking. Indeed, prior exposure to another potential gateway drug, alcohol, was found to have no effect on subsequent cocaine self-administration per se but produced greater motivation and compulsive-like cocaine seeking under a PR schedule of reinforcement. However, we observed no differences between the WIN-exposed and control groups in adulthood when we used a PR schedule of reinforcement to examine whether rats with prior exposure to WIN express alterations of the motivation to self-administer cocaine.One limitation of long-term behavioral studies in adolescent rats, including the present study, is that puberty in rats is relatively short . Compared with adults, rats that are allowed to self-administer cocaine during adolescence have been shown to be more vulnerable to cocaine addiction. Unfortunately, in the model of cannabinoid exposure during adolescence , cocaine self-administration can only be studied starting in late adolescence and continuing into adulthood because rats exit puberty by PND60. Because of this limitation, one possibility is that cannabinoid exposure during adolescence may affect cocaine intake in adolescence. The present results demonstrate that chronic exposure to cannabinoids does not facilitate the acquisition of cocaine self-administration or compulsive-like cocaine intake in adulthood, hydroponic table measured by the escalation of cocaine self-administration and PR responding in a relevant model of cocaine use disorder.

These results suggest that cannabinoid exposure per se is unlikely to be causally responsible for the association between prior cannabis use and future cocaine use in adulthood as purported by the gateway hypothesis. However, we found that cannabinoid exposure produced long-lasting increases in irritability-like behavior, which may indirectly facilitate the emergence of social conflicts and other mental disorders that may contribute to the abuse of drugs other than cocaine. Additionally, the cross-sensitization between WIN and cocaine in adolescence—which was not observed in adulthood—may highlight a short-term increase in the vulnerability to cocaine-induced behaviors. In summary, the present results showed that cannabinoid exposure during adolescence in rats produced cross-sensitization to cocaine in adolescence and a long-lasting increase in irritability-like behavior in adulthood. However, it did not facilitate the acquisition or escalation of cocaine self-administration or compulsive-like responding for cocaine in adulthood.Marijuana is the most widely used controlled substance in the world . In 2016, 192.2 million people used marijuana . Regular marijuana use, particularly initiated in adolescence, is associated with a range of adverse consequences, including poor cognitive and educational outcomes, low self-reported life satisfaction , downward socioeconomic mobility , psychiatric illness , marijuana-involved injury , and substance use disorders . Perceived risk and perceived availability of marijuana have historically been important drivers of adolescent marijuana use, and often targets of interventions to prevent or reduce adolescents’ use . However, these relationships may be changing. Most extant research on the changing associations between adolescent perceived risk, availability, and use of marijuana has been conducted in the United States , where 28 states and the District of Columbia have legalized medical marijuana since 2000, and 10 states and DC have legalized recreational marijuana since 2012 .

In this context, more adolescents now perceive no/low risk of marijuana use, but the prevalence of marijuana use has not increased simultaneously . Research on changes in the individual-level association between no/low perceived risk and use has been mixed. Some have found that the association weakened in recent years , while others have reported that it strengthened or remained stable . Additionally, perceived easy availability of marijuana has largely declined among US adolescents . Evidence suggests that the association between perceived availability and use of marijuana has remained strong and stable over time . Understanding these relationships is particularly important in light of recent liberalization of marijuana access, as perceived risk and availability are two key mechanisms through which legalization could impact use. In this study, we focus on the Southern Cone context for two reasons. First the Southern Cone has recently experienced changes in marijuana regulation, which could impact perceived risk and availability. Second, trends in adolescent marijuana use and perceived availability are different from those in the US, which could suggest distinct relationships between perceived risk and availability and use of marijuana. In 2013, Uruguay enacted a law providing the government full regulation over the large scale production and sale of recreational marijuana. Adults in Uruguay can purchase marijuana at pharmacies, grow marijuana at home, or acquire it through a cannabis club . In Argentina, possession of marijuana for personal use continues to be illegal ; however, a 2009 court judgment marked the beginning of a paradigm shift in the criminalization of marijuana since it raised a contradiction between Law 23,737 and Article 19 of the Constitution, which protects individuals’ freedom from state regulation . In 2017, Argentina approved access to medical marijuana under specific circumstances . In Chile, marijuana is decriminalized, a limited set of cannabis-based pharmaceutical products are available for medical use, and a new bill allowing other sources of access and formulations is under debate .

Since the early 2000’s, past-month adolescent marijuana use has increased in Uruguay , Chile , and Argentina . These trends are distinct from the US where marijuana use has remained stable , and from other South American countries where past-year use is less than 5% . Although perceived risk of marijuana use has decreased in both the Southern Cone and the US, perceived availability has increased in the Southern Cone, but decreased in the US . We know of no study that has assessed the individual-level relationships between adolescent perceived risk, availability, and use of marijuana in the context of the Southern Cone. Such research may inform the priority and scope of context-specific public health interventions to prevent adolescent marijuana use and help identify the drivers of use during these historical shifts. As more regions debate or enact policies to decriminalize or legalize marijuana use, the impetus for cross-country comparisons increases. Individual-level data from adolescents enrolled in secondary education in Uruguay, Chile, and Argentina were obtained from the National Surveys on Drug Use Among Secondary School Students . These cross sectional surveys, carried out every 2–3 years, collect information on substance use and related risk factors. The sampling design and survey instruments are similar to the Monitoring the Future Surveys and were implemented comparably across countries. Surveys were self-report and administered confidentially in students’ classrooms. The sample included 8th, 10th, and 12th graders in schools classified as public, private, and other in mostly urban areas. Net secondary school enrollment was 80–90% in Chile and Argentina over the last decade and increased from 67.6–82.8% from 2007 to 2016 in Uruguay . The sample was selected via clustered, multistage random sampling from areas with 10,000+ and 30,000+ inhabitants in Uruguay and Chile, respectively, greenhouse tables and schools with at least 20 students in the grades under study in Argentina. In Uruguay and Argentina, strata were types of school within urban areas of geographical regions in each country; primary sampling units were schools followed by classrooms. In Chile, strata were school type by grade within mostly urban areas and primary sampling units were classrooms. Individual-level survey weights were used. Recent school cooperation rates ranged from 76–86%. This study was determined not human subjects research by the University of California, Davis Institutional Review Board.Consistent with prior studies from South America and the US, our results indicate that the less risk an individual attributes to marijuana use, the more likely he/she is to use marijuana . However, in the Southern Cone countries, the overall magnitude of this association weakened, although it strengthened again most recently in Argentina. This suggests that risk perceptions became a weaker correlate of adolescent marijuana use over time. There are several implications of these results. First, given the overall increase in the proportion of adolescents who perceive marijuana use to pose no/low risk of harm, marijuana use would have likely increased to a greater degree in the Southern Cone had the risk/use relationship not weakened. Second, factors other than risk perceptions, such as marijuana availability, may have played a greater role in the increase in adolescent marijuana use observed during our study period. This highlights the need to consider changes in multiple individual and environmental determinants of marijuana use. Third, there may be a cross-national weakening of the risk/use relationship. We found this trend in all Southern Cone countries, and some have identified the weakening of this relationship in the US as well . This would suggest that risk perceptions may be, at least in part, shaped by broader societal norms that extend beyond local or national context. Increases in global information sharing via internet use, social media, and international news coverage may contribute to this trend .Consistent with extant research in Europe and the US , we found that adolescents who perceive marijuana to be easily available are more likely to use marijuana. However, the stability of this association varied over time and between countries.

In Chile, the availability/use association weakened, and became increasingly similar to the risk/use association, both in magnitude and trajectory, when risk and availability were modeled together. In contrast, the relationship between availability and use strengthened in Argentina and Uruguay, becoming stronger at times than the relationship between perceived risk and use in both countries. However, because we were not able to model both variables together in Argentina and Uruguay due to finite sample limitations, it is unclear how the associations relate to one another. Variation in the relationship between perceived availability and use of marijuana over time and between countries may be explained by several factors. First, different trends in availability by country may explain differences in the contribution that perceived availability makes to marijuana use. In Chile, perceived availability generally declined from 2001 to the late 2000’s and then increased until 2016, though at lower rates than use. For example, marijuana availability may depend on where individuals buy, grow, or use marijuana, neighborhood police presence and enforcement of laws, or norms about diversion of marijuana to youth . Second, alternative contributing causes of marijuana use may have arisen in Chile to a greater extent than in Uruguay and Argentina, displacing the contribution that perceived availability make to marijuana use. Such factors may include changes in peer or family substance use , changes in the illegal drug market , or social and cultural changes toward marijuana, influenced by strong lobbying for drug policy reform–particularly for cannabis– in a context of massive social movements among students . While examination of such exposures was outside the scope of the current study, future research should examine whether the contribution of perceived availability and risk to marijuana use is moderated by other potential contributing causes in the local environment. In Uruguay, the increase in perceived availability is not surprising, as the 2013 law created a concrete path to marijuana access for adults. Therefore, greater perceived availability in Uruguay likely corresponds to greater actual availability. For example, it is possible that a surplus of self-cultivated marijuana has tipped over into the streets. Second, even though minors cannot buy it, marijuana may seem more accessible because it sold to adults in pharmacies. Third, there may be increased exposure to marijuana use and contact with peers or family members who use marijuana, which could predictably result in a growing sense of availability. Our findings provide several insights about the availability/use association. First, in this region, where marijuana regulation is becoming progressively liberal and where adolescent marijuana use is increasing, perceived availability may be an increasingly important driver of marijuana use trends . Second, given the strengthening of the availability/use relationship in Argentina and Uruguay, and the high prevalence of perceived easy availability in all three countries, public health professionals in the Southern Cone may consider devoting additional resources towards regulating and intervening on the pathways by which adolescents gain access to marijuana. Relatedly, our findings raise questions about how perceptions of availability relate to real access to marijuana, including how adolescents most often obtain marijuana and whether modes of acquisition have changed over time.

These stigmatizing views of Hmong-American cultivators affect all cannabis growers. Anti-cannabis pressure creates a precarious state of impermanence — a season’s crop might be destroyed, infrastructure confiscated and investments of limited resources lost at any moment, disallowing longer-term investments. The impermanence makes noncompliance and deleterious environmental and health effects more likely, thereby perpetuating perceptions of cannabis cultivators as nuisances and dangers. As enforcement makes private land cultivation more risky, cultivators move “back up the hill,” namely onto ecologically sensitive public lands, thus substantiating characterizations of cannabis growers as criminal polluters. These stigmas even spread to county residents who do not grow cannabis themselves but if perceived to assist cannabis cultivation can face social sanctions. Meanwhile, well-resourced cultivators have an advantage over small-scale producers. They can protect their crops from visibility and complaints by concealing them on large plots of land or inside physical infrastructures ; and for white growers there is the anonymity of not being marked as ethnically different and therefore subject to heightened scrutiny. Greater access to capital, land and racial privileges insulates some from visibility and criminalization, resulting in uneven development and disparities in California’s expanding cannabis industry. Additionally, jurisdictions like the Siskiyou municipalities of Mt. Shasta and Weed are welcoming regulated cannabis commerce, thus capitalizing on its expulsion from the rest of Siskiyou and benefiting entrepreneurs with social capital and network access to successfully navigate complex public regulatory systems.After a century of cannabis’s criminal exclusion in California, grow table state voters have elected to integrate cannabis farmers into civil regulation.

An important facet of evolving cannabis regulations is local determination. As one interviewee pointed out, a 1-acre farm might be permitted in rural San Joaquin County but would not make sense in downtown San Diego. Yet, when cannabis cultivation is disqualified from consideration as agriculture by localities, as it has been in Siskiyou County, it can be substantively recriminalized and placed beyond the regulatory reach of civil institutions. Prohibitionist strategies that blur lines between civil and criminal enforcement lead to penetrating forms of visibility and vulnerability that produce inequity and disparity. The result, as this case illustrates, can be a narrow, exclusive definition of agriculture that affirms dominant notions of land use and community. The definition of cannabis cultivation as agriculture by the CDFA creates an opportunity for service providers and regulators — including agricultural institutions, public health departments and environmental agencies — to craft programs and policies that openly address the negative impacts of production. Owley advises that “if we treat cultivation of marijuana the same as we treat cultivation of other agricultural crops, we gain stricter regulation of the growing process, including limits on pesticide usage, water pollution, wetland conversion, air pollution, and local land-use laws.” Presently, however, many agencies are being enlisted in locally crafted criminalizing efforts, thus limiting their ability to work cooperatively with cultivators and address issues through customary civil abatement processes. Though unregulated cannabis cultivation can pose threats to public health, safety and welfare, police enforcement is only one of many possible ways to address it. Siskiyou’s cannabis cultivators experience familiar agricultural challenges around access to land, water and credit. These challenges are amplified without technical assistance or institutional support. If recognized statewide as farmers, these cultivators would be better positioned to access agricultural training and support services, thus addressing ecological and social concerns around cannabis production.

Additionally, new cannabis cultivators might be considered “beginning” farmers according to the CDFA, and minority farmers, including Hmong-Americans, who experience poverty at twice the national rate , would be considered “socially disadvantaged” under the California Farmer Equity Act of 2017 . Farmers with these designations would, in fact, be prioritized for technical assistance and support from farm service providers — if, that is, they were recognized as farmers. Uniformly treating cannabis cultivation as agriculture would also help enable the collection of accurate and robust data by researchers. This information base is necessary if agricultural institutions are to take an assistive and educational orientation toward cannabis farmers. Continued enforcement tactics that amplify distrust, frustration and confusion will further hinder data collection , leaving little basis to understand basic dynamics of complex, interdisciplinary systems like agriculture . In a criminalized situation, it is inevitable that information is metered and brokered by community leaders in ways that inhibit full understanding of cannabis cultivation. We suggest, for all these reasons, that a decisive break with enforcement-led, prohibitionist trajectories is needed and that agricultural institutions lead civil policy development and support farmers who cultivate cannabis. Agricultural service providers could play a leadership role in addressing the pressing needs of farmers — both those impacted by and engaging in cannabis cultivation. Yet, UC Agriculture and Natural Resources Cooperative Extension advisors, for instance, consistently report that they are currently prohibited from engaging with cannabis issues . Additionally, many county-based agricultural commissions, Siskiyou County’s included, feel that cannabis is not an agricultural enterprise and therefore do not see its cultivators as their clientele. Without leadership from agricultural institutions and agencies, the expanding cannabis cultivation industry is left to develop unevenly across the state — with wealthy private interests capitalizing in some locales while vulnerable and unregulated growers may retreat, to avoid criminalization, into ecologically sensitive areas.

UC ANR and CDFA have an opportunity to fulfill their missions and facilitate, for a burgeoning farming population, greater parity in farmer rights, capacities and resource access. Identifying the factors limiting imperiled wildlife populations requires an understanding of all influences affecting population growth and persistence. The geographic range of the fisher, , a medium-sized mesocarnivore that inhabits northern North America, has contracted significantly over the past century. Several factors potentially explain this contraction, including trapping and habitat alteration associated with fire management and logging throughout the early 1900s . Recent conservation efforts, such as reintroductions and forest restoration to improve habitat, have helped to increase the fisher’s range from a range-wide low of 43% back to 68% of its historical range. However, recent expansions were concentrated primarily in the central and eastern portions of the fisher’s range. Fisher populations in the Pacific states currently occupy only 21% of their historic distribution in this region and have not expanded, even in some regions with ample available suitable habitat and limited forest fragmentation. Fishers were extirpated from the state of Washington and northern and central Oregon prior to reintroductions to these regions from northern and eastern populations. Isolation and failure of population expansion in this portion of their range has prompted the United States Fish and Wildlife Service to deem these populations in these Pacific states a West Coast Distinct Population Segment and propose them for listing under the US Endangered Species Act as a threatened species. In 2015, the California Department of Fish and Wildlife listed the southern Sierra Nevada population of fishers, vertical rack but not the northern California population, threatened under the California Endangered Species Act. California contains two genetically and geographically distinct native populations of fishers within this DPS. The northern California population inhabits the coastal and southern Cascade mountain ranges and is the larger of two California populations. The southern Sierra Nevada population is considerably smaller, thought to contain approximately 300 individuals with fewer than 120 breeding females. The USFWS considers five potential limiting factors as merits for listing: 1) destruction or modification of the habitat or species’ range; 2) overutilization for commercial, recreational, scientific or educational purposes; 3) disease or predation; 4) the inadequacy of existing regulatory mechanisms; or 5) other natural or manmade factors affecting its continued existence. Investigation into the frequencies of different causes of mortality can lend information to several of these concerns, most specifically factors 2, 3, and 5. Though several studies on western fisher populations have included descriptions of isolated cases of mortality for fisher, a systematic, large-scale investigation into cause-specific mortality as determined through full necropsies has not been conducted, specifically within the West Coast DPS . Since 2004, several long-term studies of the California fisher populations have been initiated investigating demographics, habitat utilization, and mortality, and we took the opportunity to investigate fisher mortality across projects for a more comprehensive examination throughout California.

Fishers were collected through three long-term projects in California , including one on the northern California population and two in the southern Sierra Nevada: the Sierra Nevada Adaptive Management Project , and the USFS Kings River Fisher Project . The HVRFP project area was located in northwestern California on the Hoopa Reservation and adjacent private lands and federal United States Forest Service public lands. The HVRFP personnel monitored fishers from the ground using telemetry approximately 1–2 times per week . Both southern Sierra Nevada fisher projects were conducted on the Sierra National Forest in the northern and central portions of this population’s range. Fishers from the SNAMP project were located 3–6 times per week via aerial telemetry , while the KRFP personnel located each fisher via ground telemetry 2–3 times per week . In all projects, fishers were captured in box traps modified with plywood cubby boxes to minimize environmental stressors. Each fisher was fitted with a VHF radio-collar and monitored via radio-telemetry. Radio-collars were equipped with activity or mortality sensor. Inactivity on two consecutive location attempts separated by more than 24 hours or a single mortality signal from telemetry collars prompted attempts to recover carcasses as soon as was practical. When a fisher carcass was recovered, project biologists identified and recorded a suspected cause of mortality. Field based mortality determinations were constructed from evidence found at the immediate mortality site and the condition of the carcass . Recovered fisher carcasses were stored in a -20°C freezer until further analysis. Fishers were subject to a complete necropsy performed by a board-certified veterinary pathologist specializing in wildlife at the University of California, Davis Veterinary Medical Teaching Hospital or the California Animal Health and Food Safety Laboratory System on the UCD campus. Additionally, any uncollared fishers that were collected opportunistically from the field within or near project areas were necropsied. For each fisher carcass, age was determined by pulp-cavity closure or enumeration of cementum annuli of an upper premolar. Fishers were classified as kits if they were altricial and dependent on mothers-milk for nourishment , juveniles if weaned and <12 months of age, sub-adults when between 12–24 months of age, and adults when  24 months of age. Ancillary diagnostic testing was performed based on gross and histologic findings and consisted of molecular diagnostic tests to confirm a viral etiology, toxicological screening of selected Thissues, forensic genetic tests of swabbed ante-mortem bite wounds to identify species of predators, and serology to determine exposure to three carnivore pathogens: canine distemper virus , canine parvovirus-2 , and Toxoplasma gondii. Serological assessment and titer cutoffs were performed via indirect fluorescent-antibody assays on uncoagulated blood collected by sterile cardiac puncture. For both CDV and T. gondii, detection of both antibody isotype IgG, which persists for extended periods, and the short-duration antibody isotype IgM was used, while only detection of isotype IgG was used for CPV . Isotype IgM was utilized for selected pathogen assays since recent or acute infections from these pathogens may predispose individuals to certain causes of mortality. Predation was considered the cause of mortality if ante-mortem hemorrhage was observed and associated with bite, claw or talon wounds. In addition, we followed up visible field signs of predation for which ante-mortem hemorrhaging could not be determined with forensic DNA testing of Thissue around putative bite wounds or tooth marks. Mortalities were classified as “natural disease” if they exhibited clinically significant infectious or non-infectious factors that were considered by the pathologist to represent the primary cause of death. Mortalities were classified as “poisoning” if an individual had acute clinically significant signs of toxicosis associated with toxicant exposure . Fishers that died directly from anthropogenic factors were classified as “human-caused.” Vehicular strike was considered to be the cause of death when carcasses were recovered on or near roads combined with evidence of blunt trauma. If a fisher carcass had insufficient Thissues for a necropsy, severe autolysis or a lack of forensic evidence, its cause of death was classified as unknown.StaThistical analyses were performed using R studio version 0.98.507 and the “mlogit” packag. A kappa staThistic for test agreement was calculated to assess the strength of test agreement between field biologist-suspected cause of death and necropsy-confirmed cause of death .

Remarkably, Irvine has 9.7% of the Hispanic population, and Santa Ana—77.3%. In Outsiders, Howard Becker defines three types of social control of cannabis use: limiting supply and access to the drug; keeping nonusers from discovering that one is a user; defining the act as immoral. Since Becker published his book, cannabis has been depenalized, decriminalized, and finally legalized in California. Although the situation has significantly improved in terms of supply and access to cannabis, the stigmatization of cannabis use is still a pressing issue in the legal cannabis market. The war on drugs generated various misconceptions about cannabis, which detrimentally affected public perceptions. First, despite scientific research showing that cannabis is no more harmful than nicotine or alcohol, some people still believe that cannabis is a gateway drug to heavier substances that induces criminal activity and violence. Second, although most people recognize the medicinal benefits of cannabis , they continue to disfavor the recreational use of cannabis, perceiving it as a non-conforming and risky behavior and its users as weak and non-productive members of society. Finally, people who tolerate the recreational use of cannabis in private spaces do not always accept its public display and consumption. Agreeing with legalization as a concept, Californians are not ready to embrace it entirely and allow dispensaries in their own neighborhoods—this occasionally leads to their obtaining court rulings against cannabis-growing operations. The drug problem cannot be adequately understood without examining the underpinning issues of poverty and disadvantage . There is nothing inherently criminogenic about drugs, nor drugs necessarily relate to poverty. Stigmatization of drug use is a product of a culture in which the consumption of pleasurable intoxicants is deemed intolerable and punishable. Drug use is a heavily moralized territory, indoor grow shelves and the lower social strata suffer worse outcomes than more affluent people for the same drug-related behavior .

The literature on the history of drugs portrays drug regulation as a moral tale, in which the “blurry lines between us and them, privileged and repressed, strong and weak, keep getting rewritten as the boundaries between good and evil” . Existing at all social levels, drug use is recognized as a problem in specific social contexts—namely, it is clustered in the communities suffering already from multiple socio-economic difficulties . Even if the number of cannabis arrests is declining every year, Hispanics and African Americans continue to be disproportionately arrested. In California, in 2019, Hispanics accounted for 41.7% of cannabis felony arrests, African Americans for 22.3%, and whites for 21.3%. Despite the fact that cannabis consumption rates are higher among whites, they are less likely to be arrested for cannabis-related offenses . The idea behind socio-spatial control is that deviance should be contained within designated territories, i.e., if objects, practices, and behaviors do not fit the existing social order, they are to be spatially excluded. In this chapter, I tested the reverse hypothesis, i.e., if things are geographically put out of place, it means that they are viewed as socially undesirable and inappropriate. The statistical analysis shows that city governments act as moral entrepreneurs when deciding whether they want to forbid or allow legal cannabis businesses. The prohibition era stereotypes continue to influence the development of the legal cannabis market: most jurisdictions decide to keep aloof from spoiled identities and tainted places associated with cannabis use, even at the cost of not reaping financial rewards. On the contrary, economically disadvantaged communities with a larger Hispanic population are more likely to permit cannabis dispensaries because: they have higher financial incentives, and they have lower reputational risks. Since these communities are already marginalized and associated with crime, disadvantage, and social exclusion, having legal cannabis dispensaries will not exacerbate their stigmatization.As of May 2022, 38 states permit medical cannabis and 19 states permit recreational cannabis.

These policies have numerous potential implications for public health, including changes in the epidemiology of cannabis consumption and associated health outcomes. States regulate cannabis in varied ways, but many cede substantial powers to local governments. Within the bounds of state law, local authorities may determine the number and type of commercial cannabis businesses allowed, if any. They can also regulate locations of retail cannabis outlets, hours and days of sale, types of products sold, packaging, advertising, tax rates, and clean air requirements. Guidelines for state and local cannabis control policies regulating cannabis are based on alcohol and tobacco research. Recommended policies may protect public health by limiting cannabis availability and potency and by encouraging safer modes of use. In states with legal cannabis and local control, city and county governments can advance health equity by adopting health-promoting cannabis control policies and ensuring that they are fairly applied across the population. Little is known about local variation in cannabis control policies or to whom these policies apply. Previous studies surveyed local cannabis control policies following recreational cannabis legalization in Colorado, Washington, and California. All found wide variation, primarily between jurisdictions that banned commercial cannabis businesses and those that allowed all or most commercial activities. However, none of these studies characterized the populations affected by distinct policy approaches. Variation in local laws is important, because if policies that protect public health are adopted in socially advantaged communities but not in disadvantaged communities, health disparities may be exacerbated. For example, uneven application of smoke-free tobacco laws across localities was linked to racial/ethnic and socioeconomic disparities in tobacco related disease. Anticipating such disparities can inform appropriate public health responses.

Previous studies show that cannabis outlets, particularly illegal ones, are disproportionately located in less advantaged communities. Studies from alcohol control show that local governments can play a role in both creating and mitigating undue burden of alcohol outlets in vulnerable communities through local planning, zoning, and public health regulations. Similar provisions could be needed to protect communities from uneven distributions of legal or illegal cannabis outlets. In this study, we characterized the demographic and socioeconomic characteristics of communities subject to different types of local cannabis control policies. We considered 3 levels of policy measures: overall bans on cannabis businesses, restrictions on cannabis availability, and individual cannabis control policies. We hypothesized that policies designed to protect public health would be less common in socially disadvantaged communities. We focused on 12 counties in California, where adult use of recreational cannabis was legalized on November 9, 2016, and retail sales were implemented on January 1, 2018.We assessed local cannabis control polices for 12 of California’s 58 counties and all the incorporated cities within them. These counties were selected to capture a range of sizes, sociodemographic compositions, political orientations, and cannabis policy approaches. City policies apply within incorporated city borders, indoor garden table and county policies apply to areas outside of incorporated cities . We defined “jurisdictions” as the set of incorporated cities and unincorporated county areas because these are mutually exclusive and collectively exhaustive geographic areas to which distinct policies apply. The 12 counties included 230 distinct cities and 11 unincorporated county areas , covering 59% of the California population . Using a legal epidemiological approach, we systematically coded characteristics of cannabis policies in all 241 jurisdictions and then linked these policies to data on demographic and socioeconomic factors to characterize the affected populations. For each jurisdiction, we identified the corresponding local government’s online searchable database of currently applicable laws. All code and ordinances are publicly available under the California Public Records Act. We downloaded all legal text pertaining to cannabis by using the search term “cannabis OR marijuana OR marihuana.” Across jurisdictions, relevant legal text ranged in length from 1 paragraph to thousands of pages. Five authors reviewed the text using a structured data collection instrument to capture the presence or absence and content of prespecified provisions in each jurisdiction’s cannabis law. Policy data were collected and managed using REDCap electronic data capture tools hosted at the University of California San Francisco. The data collection instrument was iteratively piloted and refined as new policy approaches were uncovered. To ensure accuracy, all jurisdictions were double coded by 2 analysts until achieving greater than 95% agreement. Policy data collection and coding were conducted from November 2020 to January 2021. The complete protocol and data collection instrument are provided in Appendices B and C .California state law specifies a minimum set of policies that apply to medical and recreational cannabis statewide. However, localities retain considerable discretion. We collected cannabis policy measures, guided by an established taxonomy of all possible cannabis policies developed by affiliates of the Alcohol Policy Information System. From this comprehensive taxonomy, we measured all policies that could be applied at the local level in California given state law, varied across jurisdictions within California, were more restrictive than state law, and were plausibly related to public health according to previous evidence, recommended public health best practices, and expert opinion. We captured the greatest detail on restrictions related to cannabis availability and retail sales, because these are major levers for modifying population-level consumption, and existing evidence suggests that policies regulating retail sales are the key component of state laws linking legalization to consumption and problems. Appendix A, Table A describes these local policies, relative to state law.To characterize the populations exposed to different policy approaches, we included a range of demographic and socioeconomic characteristics from sources including the US Census Bureau and Geolytics.

We considered sociodemographic characteristics related to health disparities, including age, race/ethnicity, gender, educational attainment, poverty, unemployment, median income, household composition, urbanicity , home ownership, and population change. We also assessed the density of social organizations as a measure of social capital and density of general retail businesses as a measure of economic development. Appendix A, Table B provides additional detail on each covariate. In addition to considering each sociodemographic characteristic individually, to help synthesize the overall pattern of results, we created a binary measure of social advantage by entering all of the jurisdiction-level sociodemographic measures into a principal components analysis and dichotomizing the resulting first component at the median. In sensitivity analyses, we considered measures of social advantage dichotomized at the 75th and 90th percentiles.We found substantial local variation in cannabis control policies. Of 241 jurisdictions, 83 permitted at least 1 form of commercial medical or recreational cannabis business . The largest distinction in regulatory approaches across jurisdictions was between those that banned all forms of medical and recreational cannabis businesses and those that permitted them all . Between these extremes, 5 jurisdictions permitted all types of medical businesses but not recreational businesses; 14 permitted cultivation, distribution, manufacture, and testing but not retail; and 5 permitted retail only. Jurisdictions with nonzero residential populations permitting at least one form of medical or recreational retail cannabis enacted a range of cannabis control policies . Most jurisdictions required local permits for retail sales , limited hours of sale , taxed retail purchases , restricted the density of outlets permitted per land area or population , and adopted operating standards for upkeep and safety . Bans on on-site consumption, which protect workers and visitors from health hazards such as secondhand smoke exposure, were present in 74% of jurisdictions. Less common were public health tools such as restrictions on marketing or advertising , server training requirements , limits on product types or potency , or social host liability .For the 238 jurisdictions with nonzero residential populations, Table 1 compares the population characteristics of jurisdictions banning all cannabis businesses versus those that permitted 1 or more. All-out bans on all cannabis businesses were more common in areas with higher socioeconomic status. Populations in jurisdictions permitting commercial cannabis, by contrast, were on average less educated, with lower median income, more poverty, higher unemployment, and more crowded housing. Cities and unincorporated areas allowing cannabis businesses were also slightly older and had greater proportions of Black and Latinx residents, and fewer Asian and White residents. Population density, population growth, renters, non-family households, and densities of general retail and social organizations were also greater in jurisdictions permitting cannabis businesses.For the 68 jurisdictions with nonzero residential populations that permitted at least 1 form of cannabis retail, Table 2 shows the characteristics of populations residing in jurisdictions with varying numbers of public health restrictions on retail sales and cannabis availability.

As I discussed above, cannabis prohibition and cannabis legalization are not separate processes; these are two dialectically united phenomena that interact, contradict, negate, and reaffirm each other. Socio-legal scholars, who are interested in cannabis as a criminal justice issue, often overlook the fact that control does not exist without resistance and that criminalization and legalization are two sides of the same coin. It is impossible to understand lawmaking processes without considering the work of mobilized groups of citizens challenging the unfair laws and shifting agendas of resourceful players. As I show below, defining the “drug problem” is not a prerogative of mighty actors or institutions. Some less powerful actors can create and promote alternative narratives about drugs and drug users and ultimately succeed in changing the governing norms and public opinion. The ongoing cannabis legalization in California offers a clear illustration of how social movements can become a local source of power and foster ideational change. It was the first state to prohibit recreational use of cannabis in 1913 and the first to allow its medical use in 1996. Pro-cannabis social movements emerged in response to the Controlled Substance Act that classified cannabis as a Schedule I drug . According to Andreas Glaeser , change becomes possible when the state fails to positively validate people’s understandings of the social world. Understandings contribute significantly to the stabilization of political institutions, but for this to happen, they need to be continuously validated.

There are three modes of understanding based on: interpretations, emotions, and senses. In the case of cannabis, drying rack cannabis the de-fetishization of the prohibitionist policies started in the 1960s, when new scientific evidence, dissaThisfaction with authorities, and people’s own experience challenged the domain of unquestioned background assumptions about cannabis and its users. The first objection to the prohibitionist assumptions came from the scientific community, which provided a new interpretation of cannabis. Although Nixon disowned the Shafer Commission’s report , which called for the decriminalization of cannabis possession, its results were spreading in society, along with the La Guardia Report of 1944. From the 1970s, scientific evidence proving the medical benefits of cannabis and demystifying its deleterious effects was multiplying, but the government continued to ignore it. The scientific community was calling for thorough research of the chemical properties, pharmacological qualities, and therapeutic applications of cannabis . More and more studies had shown the possible benefits of cannabis use. However, the scientific evidence was constantly downplayed by the federal authorities and the National Institute of Drug Abuse, who continued to fixate on presumed adverse effects of cannabis . For instance, the Reagan administration ignored the National Academy of Science’s report published in 1982, which questioned the effectiveness of full prohibition and recommended removal of criminal sanctions. Under the democratic Clinton presidency, a study co-authored by Harvard Medical School and Yale University showed the efficacy of cannabis for a wide range of ailments.41 Yet, once again, scientific findings did not change the anti-cannabis course of the political establishment; on the contrary, the drug-war budget doubled, and the record number of Americans were arrested on cannabis charges in those years .

The second challenge to the prohibitionist status quo was a growing dissaThisfaction with the US drug policy and the defiance of state authority. Cannabis use became a form of protest, a central symbol of the counterculture, and a ritual that demonstrated the willingness of young Americans to run risks with their peers . Many college students began smoking cannabis to protest the war in Vietnam. The government responded with harsher enforcement of drug laws: cannabis-related arrests rose from 18,000 in 1965 to 220,000 in 1970. That inevitably amplified protest movements. According to Patrick Anderson, the legalization movement began on August 16, 1964, when a young man walked into a police station in San Francisco, lit a cannabis joint and asked to be arrested . Later that year, his lawyer launched the Legalize Marijuana organization , which sponsored the first pro-cannabis demonstration in America. In sum, the legalization movement was developing in response to political threats, confronting the mythology of “reefer madness” and persuading Americans that the time had come to change political priorities and put an end to the incarceration of young people for using a mild intoxicant . The third challenge to the prohibitionist discourse arose at the level of individual senses. An increasing number of people who used cannabis realized that it was no more dangerous than alcohol. The fact that cannabis was classified as the most dangerous drug, causing more damage than cocaine, opium, or methadone, sounded preposterous to those who had experienced cannabis effects. Thus, less and less people believed in the myths propagated during the anti-cannabis campaign. In 1975, psychiatrist and social activist Tod Hiro Mikuriya wrote: “Marijuana use in America is reminiscent of the era of Prohibition, in that almost 30 million people have smoked pot and the police of the 180 million other Americans are trying to prevent them from doing so. Despite vigorous efforts of society to regulate by deterrent legal sanctions, they have obviously failed. The use continues to escalate. In fact, marijuana has become a permanent part of American society. Since those who try and continue to use pot find it enjoyable, and many more people are trying it all the time, marijuana use is clearly here to stay.

The time has passed when prohibition against personal use and possession should have been repealed” . All three factors—scientific evidence, dissaThisfaction with authorities, and personal experience—made Americans more susceptible to the proclaimed dangers of cannabis. And this, in turn, raised political dissidence. In the 1970s, many social activists felt that the decriminalization and legalization of cannabis were just “around the corner.” Not only scienThists and activists but also some state actors favored the depenalization of cannabis. The National Organization for the Reform of Marijuana Laws became the main voice of the pro-cannabis movement. Founded in 1970 by Georgetown law graduate Keith Stroup, the organization brought together a group of young lawyers, scienThists, civic leaders, and even politicians to fight for cannabis reform . From the very beginning, NORML was a public-interest lobby that represented the interests of cannabis users, commercial greenhouse supplies focusing on individual rights and the social harm caused by incarceration for minor drug offenses. Although its ultimate goal was the complete legalization of cannabis, in the 1970s, NORML focused mainly on the depenalization of cannabis and its removal from the list of Schedule I controlled substances. A catalyst of the national pro-cannabis movement, NORML scored its first victory in 1973 when Oregon has ended criminal penalties for smoking cannabis. Over the decade, several more states—including California—have followed suit. In 1976, California approved the Moscone Act, which made possession of small amounts of cannabis a civil instead of a criminal offense. That was the beginning of cannabis decriminalization in California: felony arrests for cannabis decreased fourfold—from 99,587 in 1974 to 19,284 in 1976 . In subsequent years, both the number of organizations working on pro-cannabis issues and the pressure imposed on the federal government increased. In 1977, President Carter asked Congress to decriminalize the possession of small amounts of cannabis at the federal level . But his plan never came to life due to the scandal discrediting his drug advisor Peter Bourne and the emergence of the grassroots parents’ organizations, which were building strong opposition to cannabis decriminalization. In 1986, the Drug Enforcement Administration finally agreed to review a petition filed by NORML and the American Public Health Association that asked to recognize the medical value of cannabis and remove it from Schedule I classification . After careful investigation, the DEA’s chief administrative law judge Francis L. Young stated that cannabis “has been accepted as capable of relieving the distress of great numbers of very ill people […] and it would be unreasonable […] for DEA to continue to stand between those sufferers and the benefits of this substance.” The judge permitted the transfer of cannabis from Schedule I to Schedule II so that cannabis could be legally available for patients. However, the DEA director ignored such recommendations . Throughout the 1980s and 1990s, the federal government and the media launched the largest anti-drug and anti-cannabis campaign. In this cultural context, the pro-cannabis movements did not have any political or discursive opportunities to bring about legal change. To a great degree, the success of social movements depends on their ability to “offer frames that tap into a hegemonic discourse” . Cannabis activists had nothing to offer; their claims did not resonate with ideas widely accepted in the broader society. The situation has changed with the AIDS epidemic, which provided discursive opportunities for politically effective framing. The narrative that cannabis could be medicine is not new; it has existed for centuries, despite the efforts of the federal drug enforcement to suppress it. But in the 1980s and 1990s, the medical conception of cannabis had reemerged and developed into a powerful moral agenda .

Robert Randall, a young college professor from Washington, D.C., was the Rosa Parks of the medical cannabis movement . In 1976, he sued the federal government for the right to use cannabis to treat his glaucoma. His doctor testified that the use of cannabis significantly decreased eye pressure, one of the primary symptoms of glaucoma, which kept Randall from going blind . In 1978, D.C. Superior Court established an important legal precedent: Randall won his case and became the first legal cannabis smoker since cannabis prohibition in 1937. However, Randall’s victory did not solve the problem of obtaining cannabis legally. He was not allowed to grow cannabis for himself and filed a petition demanding that the government provides him enough cannabis from the federal experimental farm at the University of Mississippi . His victory forced the Food and Drug Administration to establish the Compassionate Investigational New Drug Program, which provided government-grown cannabis for seriously ill patients. However, the program was limited to a small number of patients since many people who had received medical approval were rejected by the program . By 1991, only 15 patients were enrolled in the program. Randall’s legal precedent was a landmark victory, and social movements continued to exploit the medical discourse in the following years. Pro-cannabis activists crafted the image of cannabis as a compassionate palliative for seriously ill people and the image of cannabis users as patients, not criminals . However, such a medical frame was not very successful until the AIDS epidemic in the 1980s, which made medical cannabis an urgent issue and provided first discursive and later political opportunities for the movement. Many AIDS patients experienced wasting syndrome, and cannabis helped them stimulate appetite, retain weight, and prolong lives. As Cyrus Dioun argues, “the death and devastation of the AIDS epidemic made it necessary to discuss previously unmentionable topics” . From 1980 to 1995, over 500,000AIDS cases and over 300,000 AIDS deaths have been reported in the US. San Francisco was at the forefront of both the AIDS crisis and the medical cannabis movement. By 1993, 4% of the city’s population were living with AIDS . The outbreak of the AIDS crisis challenged the illegal status of cannabis: now, law-abiding AIDS patients had to take illegal actions that were previously unthinkable, i.e., to purchase an illicit drug on the black market to ease pain and restore appetite . The cause seemed greater than harm, and it raised sympathy and support for AIDS patients among the population. AIDS patients first tried the path that Robert Randall has opened for them: they applied to the Compassionate Investigational New Drug Program to obtain government-supplied cannabis, but the number of applications was so large that the government stopped accepting new applicants in the early 1990s . Unable to get cannabis through legal channels, AIDS patients were pushed to the illegal market where medical cannabis activists developed informal institutions that delivered illegal products to legitimate consumers . In 1991, Dennis Peron, an illegal cannabis dealer and gay rights activist, drafted and organized the passage of the San Francisco medical cannabis initiative , which recommended the State of California and the California Medical Association to include cannabis in the list of available medicines and not penalize doctors for prescribing it.