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Overall, higher wages and employer-provided health care would not only lower state and federal public assistance costs, and allow all levels of government to better target how their tax dollars are used, but it would also rightfully hold corporations accountable to their employees and thus challenge the status quo of federal and state subsidization of corporate profit. Beginning in the late 1990s and early 2000s, as part of the larger shift toward privatizing public assistance systems and putting SNAP benefits on ATM-style Electronic Benefit Transfer cards, large banks themselves have also benefitted from SNAP and other safety net programs. They have done so, in part, by way of the contracts they hold with states to help administer benefits. Specifically, regardless of the actual effectiveness of EBT-based benefits, J.P. Morgan Chase and other banks cover none of the operating and equipment costs, which are instead covered by and split evenly between states and the federal government, while reaping the benefits of large contracts, interest collected on federal reserve money held for government programs, and user penalties including EBT card loss, out-of-network-use, and balance inquiries. According to the Government Accountability Institute, for example, J.P. Morgan Chase made more than $500 million between 2004 and 2012 from the transaction fees of government benefits to US citizens. In New York alone, J.P. Morgan Electronic Financial Services has a nine-year EBT services contract with the State Office of Temporary and Disability Services worth $177 million. Furthermore, according to a 2012 study entitled “Food Stamps: Follow the Money,” the characteristics of such contracts provide other key indices of banking power and profit. The study found that J.P. Morgan Chase held contracts for EBT in 21 states, Guam, and the Virgin Islands, clone rack signaling significant market power and a relative lack of competition.

Contract terms varied widely among states, thus indicating a lack of efficiency and standards as well. Collectively, and perhaps most significantly, banks profits from government programs during both bad and good economic times: during times of economic hardship because more people enroll in assistance programs, and during times of economic strength because rising interest rates mean more profit on the money they hold to distribute to beneficiaries. Furthermore, corporate and banking control and windfall profits—enhanced and secured by neoliberal restructuring—have affected the socio-economic well-being, and thus food security, of low-income communities and communities of color beyond the struggle over wages. The trend toward bio-fuels in particular—shown in Part I to be predominantly a corporate-controlled affair— has had a direct impact on the cost of food. A 2011 Food and Agriculture study concluded that the expansion of bio-fuels production, particularly in the United States with corn-based ethanol, and in the EU with biodiesel, is at fault for the demand shock for cereals since 2000. Such control of demand has had a large impact on tight commodity markets, such as corn. US ethanol, for example, consumes 40% of the country’s corn, and 15% of global corn production. While estimates vary on the impacts, the National Academy of Sciences concluded that 20 to 40% of the global food price increases in 2008 and the growth widespread hunger were due to bio-fuels expansion. Furthermore, other studies have found that each billion-gallon increase in ethanol production yields a 2 to 3% increase in corn prices. Finally, although the Farm Bill originally intended to stave off food insecurity and support the economy, the result has been detrimental to public health. Specifically, the continued subsidization of commodity crops, and re-entrenchment of this system of supports under neoliberal political and economic restructuring, has helped produce the obesity epidemic in the United States As of 2012, for example, 96% of US cropland was dominated by grain and oilseed commodity crops.

Between 1995 and 2010, $16.9 billion in federal subsidies went to companies and organizations that produced and distributed corn syrup, high fructose corn syrup , cornstarch and soy oils. In this light, as of 2012, the United States has the highest global per-capita consumption of HFCS at a rate of 55 pounds per year. Furthermore, as of 2013, 54% of the oil consumed by Americans is soy oil primarily in the form of cooking oil, baked good, and frying fats. As can be expected from mass consumption of these products, the rates of diabetes and obesity in the US have reached alarming levels: more than a quarter of the US population, or approximately 90 million people are obese, and 21 million have diabetes. Moreover, these food-related health challenges disproportionately impact communities of color as follows: Black adults have 47.8% obesity, Latinos/as have 42.5% obesity, and Asian Americans have 10.8% obesity. Significantly, the combination of ease of access, low cost, and negative health impacts of such foods, further harms low-income communities well-being while corporations themselves continue to profit. Conservative politicians and news pundits have maintained an assault on federal anti-poverty and safety net programs, and on SNAP in particular. The attacks on federal anti-poverty and safety net programs have consistently targeted the use of SNAP by such communities by relying upon anti-poor and racist “culture of poverty” stereotypes that readily blame marginalized communities for their social and economic conditions. Leading up to the passage of the 2014 Farm Bill, for example, House and Senate Republicans—both House Republicans inside and outside the House Agriculture Committee— aimed to impose new work requirements on SNAP recipients, under the assumption that those that receive public assistance have no incentive to work; to allow states to require drug testing for SNAP beneficiaries, under the assumption that low-income people and people of color are likely to use that money to purchase drugs, or that their substance abuse is the primary cause of their hardship, not vice-versa; and to ban ex-felons from ever receiving nutrition assistance, under the belief that ex-felons no longer deserve the support of society.

Although the underlying set of beliefs remains deeply embedded within society, many of these provisions were ultimately stripped from the bill and none of those measures were included in the 2014 Farm Bill. The most pervasive myth is that people on SNAP are “not in a hurry to get off,” primarily because of the supposed lack of incentive to work and the ease of profiting off federal support. On the contrary, most SNAP recipients remain in the program for a short period of time until they become financially stable and are able to transition to self-sufficiency, with half of all new participants leaving SNAP within nine months and many others leaving the program once their immediate need has passed. Moreover, as of 2011, many SNAP beneficiaries are already working: nearly 10.3 million working families receive assistance, comprising 36% of the total program enrollment, with more than three times as many SNAP households working as those that rely solely on public assistance for their income. Moreover, 4×8 tray grow according to a 2012 Congressional Budget Office report, SNAP usage is expected to decline between 2012 and 2022, reflecting a potentially improved economic situation and declining unemployment rate. Finally, despite sustained claims of fraud that accompany efforts to cut SNAP benefits, SNAP continues to have one of the lowest fraud rates among Federal programs. According to a 2013 USDA Food and Nutrition Service report, the rate of SNAP fraud has declined from 4% of benefits down to about 1% over the last 15 years. SNAP is among the most widely used anti-poverty programs in the United States and, according to the Center on Budget and Policy Priorities, the second most responsive federal program during economic downturns, only behind Unemployment Insurance . The percentage of the population with income below 130% of the federal poverty line—the income limit for SNAP eligibility—increased substantially during the period of the Great Recession, from 54 million in 2007 to 60 million in 2009, and 64 million in 2011. During this period, the rate of SNAP participation rose among eligible households from 65% in 2007 to 75% in 2010, up to 83% in 2012, with the program expanding at a record pace of 20,000 people per day. By the end of 2014, more than 46 million people, over 14% of all Americans, were using SNAP. SNAP eligibility and use, however, varies significantly by race/ethnicity, with communities of color experiencing the highest rates of eligibility for, and use of, SNAP, particularly during economic downturns. For example, by end of 2009, SNAP was used by 12% of the US population , 28% of all Blacks and 15% of Latinos/as nationwide were using SNAP. On the other hand, only 8% of whites were using SNAP, substantially below the national average. Such trends follow racial/ethnic and economic geographies as well, with SNAP use greatest where poverty and racial/ethnic stratification runs deep. Across the ten core counties of the Mississippi Delta, for example, 45% of Black residents receive SNAP support, while in larger cities such as St. Louis, with a population of 353,064, the percentage of Black residents receiving SNAP support rises to 60%. Even in the largest cities, those with over 500,000 people, such trends remain: white SNAP use peaks at 16% in the Bronx, New York for example, while Black SNAP use peaks at 54% in Kent, Michigan.

Significantly, there are 20 counties across the United States where Blacks are at least 10 times as likely as whites to be SNAP beneficiaries, and 26 counties in the United States where over 80% of Blacks were SNAP recipients. Conversely, there are only 5 counties with more than 39% of white receiving SNAP benefits. The growth of SNAP use amidst the Great Recession has been especially rapid in locations worst hit by the housing bubble burst, and particularly in suburbs across the United States where SNAP use has grown by half or more in dozens of counties. Furthermore, this is the first recession in which a majority of low-income communities and communities of color in metropolitan areas live in the suburbs, giving SNAP and other federal aid new prominence there. The increase in SNAP eligibility and use thus mirrors the impacts of the crisis in housing and employment, and the racialized distribution of impacts of such crises. Specifically, SNAP use was found to have increased by the greatest amount in places characterized by increased poverty, increased unemployment, more home foreclosures, and increased Latino/a populations. A 2012 Congressional Budget Office report confirmed such findings and estimated that although 20% of the growth in SNAP spending was caused by policy changes, including the temporarily higher benefit amounts enacted in the American Recovery and Reinvestment Act of 2009 , the housing crisis and weak economy were responsible for about 65% of the growth in spending on benefits between 2007 and 2011, with the remainder caused by other factors, including higher food prices and lower incomes among beneficiaries. Such has been the case historically: when unemployment rose, SNAP use always did too, signaling how SNAP use has long played a role in alleviating periods of economic distress. As such, SNAP is heavily focused on the poor. According to a 2015 Center on Budget and Policy Priorities report, about 92% of SNAP benefits go to households with incomes below the poverty line, and 57% go to households below half of the poverty line . Because families with the greatest need receive the largest benefits, and because households in the lowest income bracket use twice the proportion of their total expenditures on food than do those households in the highest income bracket, SNAP is a powerful anti-poverty tool. SNAP, when measured as income, kept 4.8 million people out of poverty in 2013, including 2.1 million children, and lifted 1.3 million children above half of the poverty line in 2013. Furthermore, SNAP is also effective in reducing extreme poverty. A 2011 National Poverty Center study found that SNAP, when measured as income, nearly halved the number of extremely poor families with children in 2011 by 48% and cut the number of children in extreme poverty by more than half . That the increase in SNAP eligibility and use during the start of the Great Recession mirrored larger trends in the economy—and was patterned after long-standing racial and economic inequality—signals the need to again assert that the experience of food insecurity is one part of a larger structure that continues to affect the most historically marginalized populations.

The primary purpose of the federal crop insurance program is to offer subsidized crop insurance to producers who purchase a policy to protect against losses in yield, as well as crop revenue and whole farm revenue. Significantly, more than 100 crops are insurable. The 2014 Farm Bill increased funding for crop insurance, primarily for two new insurance products: the Stacked Income Protection for cotton and the Supplemental Coverage Option for other crops. Ultimately, with the decline in projected spending for Title I , and the increase for Title XI , the 2014 Farm Bill underwent a decline of $8.59 billion in spending on the farm “safety net.” Under the Farm Bill, the miscellaneous title includes various provisions affecting research, jobs training, and socially disadvantaged and limited resource producers, as well as livestock production and oil heat efficiency, among other provisions. The 2014 Farm Bill extended authority for outreach and technical assistance programs for socially disadvantaged farmers and ranchers, expanded support for military veteran farmers and ranchers, and created a research center to develop policy recommendations for socially disadvantaged farmers and ranchers. Finally, it reauthorized funding for the USDA Office of Advocacy and Outreach for socially disadvantaged and veteran farmers and ranchers, and mandated receipts for service or denial of service in order to increase transparency.CORPORATE POWER HAS LONG PLAYED A ROLE in the institutions, processes, practices, plants racks and infrastructure that make up the US food system: how food is produced, processed, distributed, and consumed.

Part I provides a snapshot of the state of corporate consolidation and control in the US food system then addresses the history of the US food system with regard to the relationship between the federal government, corporate consolidation and control, and structural racialization: first, from the 1930s to the 1950s with the Great Depression and New Deal farm programs; and second, from the 1950s to the late 1970s with the erosion of such programs. It then addresses the emergence of neoliberal economic and political restructuring in the late 1970s and early 1980s—characterized by privatization, free trade, deregulation, and cuts in government spending in favor of the private sector—and the emergence of the neoliberal corporate-controlled food system. Part I then elaborates upon two major domains within which corporate influence under neoliberalism remains particularly salient. The first domain is that of food production, processing, distribution, and service—with such influence exerted by way of commodity support and crop insurance programs, labor regimes, and international food aid. The second domain is that of education, research, and development—with such influence exerted by way of lobbying efforts, private funding, strategic mergers, and the “revolving door” between corporate employees and government officials. Significantly, corporations continue to exert such influence via lobbying efforts, private funding, strategic mergers, and the “revolving door” between corporate employees and government officials. Ultimately, Part I argues that the Farm Bill, from the first Farm Bill in 1933 to the Farm Bills of the 1980s onward, is defined by the long term shift from the subsidization of production and consumption to the subsidization of agribusiness, and that low-income communities and communities of color have been structurally positioned on the losing side of such shifts. It is important to note that corporate consolidation and corporate control are two related, yet different, phenomena.

Corporate consolidation can take the form of horizontal consolidation, which refers to the consolidation of ownership and control within one part of the food system, such as production, processing, or distribution; or vertical consolidation, which refers to the consolidation of firms at more than one part of the food chain, such as upstream suppliers or downstream buyers. The term “agribusiness” is often deployed in reference to corporations that exhibit one or both sets of processes within the food system. Corporate control, however, refers to the control of political and economic systems by corporations in order to influence trade regulations, tax rates, wealth distribution, among other measures, and to produce favorable environments for further corporate growth. It should be noted that corporate consolidation is a prerequisite to corporate control. In other words, it can be looked at as a two-part process: once corporate consolidation has been achieved, corporations are much better suited to assert their control over political and economic systems as they have little competition in their respective sectors and industries. Thus, as Susan George states: “It is not just their size, their enormous wealth and assets that make the [corporations] dangerous to democracy. It is also their concentration, their capacity to influence, and often infiltrate governments, and their ability to act as a genuine international social class in order to defend their commercial interests against the common good.” A New and Changing Farm Bill: Toward Low Prices and Big Buyers The period of agricultural policy between the 1930s and the 1950s was greatly informed by the Great Depression—a consequence of the stock market crash of 1929. The crash marked the disruption of capital accumulation in every sector of the economy, including agricultural production. During the 1930s, the massive drought and soil erosion that characterized the Dust Bowl intensified the impact of the Depression upon agricultural production and had far-reaching social, economic, and environmental consequences.

The Dust Bowl affected over 100 million acres and prompted the largest migration in US history within a short period of time. Approximately 3.5 million people moved out of the Great Plains states in search of work between 1930 and 1940. Pressured by the need to support remaining farmers and thwart massive farm loss, Congress passed the New Deal-era 1933 Agricultural Adjustment Act, which aimed to raise the value of crops and reduce crop production and surplus. The 1933 Farm Bill reduced agricultural production by paying farmers subsidies not to plant on part of their land and to kill off excess livestock. However, the goal of agricultural policy did not remain tied to the support of production. Rather, by the end of the 1940s, “doctrine of parity” set standards for commodity prices and undergirded the 1941 Steagall Amendment, the Agricultural Acts of 1948 and 1949, and the permanent funding of the Commodity Credit Corporation . For the next few decades, particularly between the 1950s and 1970s, agricultural production was characterized by high-yielding varieties of a few cereals , the heavy use of subsidized fertilizers, pesticides, irrigation and machinery, and their global proliferation under the “Green Revolution.” Furthermore, from 1952 onward, the “parity” farm programs of the New Deal era were eroded, as price floors were lowered and supply management was reduced. Beginning in 1973, policy changes during the Nixon Administration precipitated the drastic deregulation of the corn market in particular by dismantling New Deal era supply management policies, selling off federal grain storage reserves, and implementing “fencerow to fencerow” planting, plant growing trays ultimately promoting overproduction and the consolidation of farm operations. Simultaneously, the system of loans and land idling schemes that supported farmers was replaced with a system of direct subsidies that supported low prices for corporate purchasers by encouraging farmers to sell crops at any price and ensuring that direct payments from the government would make up the difference. Ultimately, these changes not only reflected and upheld corporate consolidation and control, they also resulted in massive farm loss: the number of farms decreased from 7 million in 1935 to 1.9 million in 1997, with the greatest drop occurring from 1935 to 1974. The changes from both the 1930s to the 1950s, and the 1950s to the 1970s, were tied to corporate power, as reflected by several key moments in the history of the Farm Bill. First, the money for production subsidies under the 1933 Farm Bill was originally generated by way of an exclusive tax on corporations that processed farm products. Yet, according to the 1938 Supreme Court case, United States v. Butler, the act’s tax provision unfairly targeted corporations and was thus deemed unconstitutional. Subsequently, under the 1938 Farm Bill, the federal government, and not a processor’s tax, would finance such subsidies, thus relieving corporations of any responsibility to maintain high commodity prices or profitable farms. Significantly, this funding structure was held in place during the shift in agricultural policy from the support of production to the support of prices by way of the doctrine of parity. The ongoing erosion of the doctrine of parity from 1952 onward, which included the lowering of price floors and reduction of supply management practices, sent farm prices crashing and ushered in a period of agricultural policy driven by agribusiness. Specifically, corporations such as Archer Daniels Midland and Cargill were instrumental in helping replace New Deal-era loan programs and land-idling arrangements with direct subsidies that supported low prices for corporate purchasers themselves.

Anticipating the 1973 Farm Bill, for example, and alongside Secretary of Agriculture, Earl Butz, Cargill and the Farm Bureau argued that crashing farm prices would be a plus. They argued that not only would greater exports and new uses such as ethanol and sweeteners remedy the drop in price, but also that farms would remain profitable with the support of government subsidies. The winners and losers were clear under such policies: corporate buyers could acquire commodity crops for record low prices that were subsidized by the federal government while farmers continued to lose their lands and their income. Such policies, furthermore, constituted part of the larger trend in corporate growth, not limited solely to agribusiness. For example, according to a 2013 Bureau of Economic Analysis, corporate profit as a percentage of GDP more than doubled between 1980 and 2013, rising from less than 5% to over 10%; before tax, corporate profit, as a percent of GDP, rose from less than 8% to over 12.5% between 1980 and 2013. Both periods, from the Great Depression and New Deal farm programs, to their erosion over the following decades, were characterized by structural racialization. Although New Deal-era legislation was geared toward pulling Americans out of poverty, it was itself a project of racial exclusion, with Black communities and other communities of color systematically barred from such supports. Southern committee members in Congress, for example, blocked efforts to include agricultural workers and domestic workers in the Social Security Act—the New Deal’s centerpiece legislation—largely because of the high concentration of black workers within those lines of work. In the 1930s, 60% of Black workers held domestic or agricultural jobs nationally while, in the southern United States, domestic and agricultural occupations employed almost 75% of Black workers, and 85% of Black women. Furthermore, although the National Recovery Administration set wages within the cotton industry at $12 a week, many Black workers had jobs that were not covered by the law and thus had their wages reduced by employers so that white workers could be paid more. Finally, Black agricultural workers were also left out of New Dealera agricultural union programs—namely the National Labor Relations Act, enacted and signed into law on July 5, 1935—while Black landowners in particular were excluded from federal farm support under the Agricultural Adjustment Administration. Significantly, the distribution of federal support during this period resulted in the dramatic decrease in the number of Black farms, from about 900,000 in 1930 to 682,000 in 1939. Although these programs were slowly eroded over the next few decades, farmers of color continued to face great hardship relative to white farmers. The period of agricultural mechanization and industrialization after World War II, marked by the widespread adoption of scientific and technological innovations is usually credited with weeding out supposedly “non-productive, inefficient” farmers. Yet farmers of color and particularly Black farmers, in the context of the uneven application of New Deal era supports and years of discriminatory practices, were at a great disadvantage during this period because they were prevented from attaining the requisite access to capital and thus economic stability for such a transition. From the late 1970s and early 1980s until today, corporations have taken on a new and more deeply entrenched set of relationships within the food system. In short, this period is defined by neoliberal capitalist expansion and corporate control that began with the global economic shocks of the 1970s and 1980s. During the 1980s, and working for the interests of multinational corporations in securing markets abroad for agricultural commodities produced domestically, Structural Adjustment Programs broke down foreign tariffs, dismantled national marketing boards, and eliminated price guarantees in the Global South. Alongside this destructive guarantee of foreign markets, the 1950s-onward trend of dismantling domestic safety net programs for farmers, guaranteeing low prices for commodity purchasers , and making up the potential loss for farmers with government direct payments continued.

Listing a female farm operator among all the farm operators may be at least correlated with a willingness to adopt new technology, diversify sales, or increase vertical integration on the dairy farm. This is a feasible hypothesis because the presence of a female operator may indicate that the farm is more open to change than many peers in the industry. Part-time farming is common in crop and beef cow-calf operations, whereas commercial dairy farm operators tend to be full-time operators. Also, in the dairy industry, a female operator of dairy farms is likely to be married to a principal operator. Having both spouses as farm operators likely implies less off-farm income and, therefore, higher financial reliance on the dairy farm’s success than for families with more diversified income sources. Moreover, dairy farms tend to have more concentrated farm incomes with crop and dairy enterprises vertically integrated rather than the diversification common among crop farms. This changes the incentives of the spousal operators to remain economically viable because it likely increases risk aversion leading to diversification of sales and mitigation of feed price volatility risk by increasing economies of scope. The COA finding of an increase in the share of women dairy operators and farms with women operators reflects three things: an actual increase in women operators playing a more prominent role, their male associates being more likely to recognize and report female operators, weed drying room and changes in COA questions that better collect previously unmeasured management activity by women.

The increase in the share of female dairy farms must be considered against the broader pattern of dairy farm consolidation, changes in dairy farm size distribution, farm characteristics, and geographic shifts . This research seeks to provide statistical evidence of differences in farm size of dairies operated by dairies with at least one female operator relative to all male operators, the share of female operators, and those operated by spouses. By considering farms with at least one female operator and/or married operators as a “treatment” group, I compare the herd size, milk or dairy sales, and total value of production, between the two treatment groups, while holding location and year constant. This chapter is structured as follows: a brief overview of previous literature on the intersection of women and agriculture, a description of COA data related to women and farm operators, a discussion of statistics, empirical method, and results, and then a brief conclusion. Research on the intersection of women and agriculture has tended to be limited in scope and by academic discipline. Previous research on the topic from an agricultural economic perspective has focused on the intersection of women and agriculture in developing countries or limited its analysis to some demographic statistics on female farm operators without much commodity distinction within the agricultural industry. Industry distinction is important because of generally held assumptions about particular commodity farms, including that dairy farms are run by spouses. Moreover, although there have been many anthropology and sociology research studies that have been done on the intersection of women and agriculture in both developing and developed countries, these have tended to be on a case study basis that are limited in geographic scope. I found little empirical agricultural economics research on the patterns over time and across states of female farmers, and I found no prior research on the economics of patterns of female operators in the dairy industry, specifically.

A recent article by Schmidt et al. summarizes the current literature on the intersection of women and agriculture, specifying that most economic literature on this subject focuses on developing nations. The article calls for further research on this topic to further characterize the change in gender demographics and collect information on influences in the economy that may have impacted or continue to impact the number of female farm operators in agriculture. Schmidt et al. outline three possible influences on the share of female farmers, including push-pull factors, characteristics of local agriculture, and the type of farming practiced. Push-pull factors refer to the influence of off-farm employment wages that may influence an individual’s decision to be an entrepreneur or push them to seek off farm employment. For this analysis, this influence could be considered on an individual basis or at a spousal level. The change incentives when both spouses’ incomes come from farming could change and push or pull one or both spouses into off-farm employment or to stay on the farm. Characteristics of local agriculture describe the general state of the region’s agricultural economy. This is accounted for by holding constant location and presenting statistics by state. Finally, Schmidt et al. suggest the influence that the type of farming might have, or farming characteristics may influence, as their results find that farms run by women tended to be smaller. There is some association of dairy farms being family-run, or spousal run, this claim is one that we provide evidence on for the dairy industry, specifically. The characterization of such influences provides insight into the possible impacts of female representation on farms across different industries. Again, the agricultural economic literature on the intersection of gender and agriculture has tended to be limited to developing countries. However, in a recent article by USDA Economic Research Service , ERS released statistics about the characteristics of U.S. female-run farms and female operators based on the 1978 to 2007 COA . Their results focus mostly on statistics of characteristics of overall U.S. female-run farms and female farm operators.

They find that 58% of all female operators have no reported off-farm labor, and that female operators of dairy farms tend to be younger than the U.S. female operators’ average age. Griffin et al. utilize the COA data over five Census rounds and discuss the impact of farm operators’ demographics on farm exit rates. They find that larger farms are less likely to exit, and those female operators are more likely to exit than male operators. However, their study includes all farms with no industry limitations. Furthermore, research on female operators’ impact and representation within the dairy industry is a point of interest because, historically, it was not uncommon for dairy farms to be run by spouses and because off-farm employment is less likely on a dairy farm than it is on other farms. Sander finds that women working on dairy farms tend to have less off-farm employment than other farm types. He outlines the role of income variability on farms run by spouses’ decision to be both spouses’ main income with off-farm work as a possible risk mitigation strategy for farms run by spouses when farm revenue is highly variable. Schultz detailed some economic theories related to women focusing mainly on developing nations. Specifically, drying rack for weed the role of family dynamics in economic choices on farms and female influence on such outcomes. Rather than taking a theoretical approach, Zeuli and King provide detailed statistics of the characteristics of farmers and their commercial farms in 13 states. They find that in 1991 the average age of females relative to males is insignificant, but that the women in their sample tended to have a higher level of schooling. Interestingly, they found contradicting results, at least based on acreage, to other studies stating that women tend to manage smaller farms, with women operating more acreage on average, but this could be heavily influenced by what they grow and location. Sociology and anthropology research on female farm labor and agriculture tends to report findings based on case studies of specific regions and industries . These papers tend to discuss social incentives, norms, or barriers that influence the gender demographics of the industries of interest and, therefore, influence female representation and the impact of management decisions on the farm. Brasier et al. discuss the history of how women identify their labor on farms. Historically, female participation in farming communities was accessed through family or marriage. Typically, women involved in agriculture were either born into a family that farmed or married a farmer. In the past women often viewed their role on the farm as farm homemakers or farm helpers, following gender norms of the times, and often because they had off-farm income or only participated in farm labor seasonally . This way of thinking about farm labor could have influenced the representation of female operators of farms. Other sociology research has documented trends in farm management through case studies on regions. Trauger finds that women are more likely to adopt sustainable agriculture. Trauger limits its scope to a few farms in Pennsylvania, finding that there may be a trend of female-operated farms to adopt socially minded practices, i.e., community education. This research helps build evidence that supports our claim that the presence of female operators can be considered a proxy variable for being adaptable to change.

It seems like a basic assumption, but there was, and remains, a large share of women that participate in farm labor that were/are married to principal operators; this trend continues today. Therefore, the research on the relationship between gender and agriculture would not be complete without mentioning research done on agricultural spouses. A large share of female operators are the spouses of a farm operators. Barlett details the typical marriage models of agricultural spousal relationships, characterizing how farm labor related to agricultural spousal relationships is defined from a social perspective and may have influenced how women viewed their labor on the farm and subsequently the data representing farm labor, historically. The role of identity for female farmers and the professional connections can be a pivotal part of female farmer participation. This research provides evidence of the change in gender demographics based on farm size for the dairy industry. It adds to the literature detailed agricultural economic analysis on the intersection of women and agriculture for the dairy industry and discusses the change in data collection and availability by one of the most prevalent data sources for agricultural data, the COA. 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 questions 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 2007, 2012, and 2017. Second, operator characteristic questions have become more detailed over the years and allowed more operators’ data to be collected. In 2002, 2007, and 2012, the COA asked detailed operator characteristic questions about up to three operators, and only one operator was able to be identified as the principal operator. However, in 2017, the COA expanded its detailed operator questions to include up to four operators and now allows for up to four operators to be identified as a principal operator. Furthermore, in 2012, the COA started asking farmers and ranchers if the secondary operators were married to the principal operator. This question was then adapted in 2017 to reflect the increase in possible principal operators identified and asked if the operator was married to a principal operator. The Census collects two categories of operators. The first category is for which detailed operator characteristics and for which at most three operators are listed per farm in 2002-2012 and at most four operators per farm are listed in 2017. Going forward, the operators for which the number per farm is limited and detailed information is provided will be referred to the “core operators”. The second category has no limit to the number listed per farm and only gender of each operator and the number per farm is provided in the data. This section detail statistics and characteristics of female commercial dairy farm operators and their commercial dairies. The number of commercial dairies with at least one female core operator increased in every state, except New Mexico, which experienced no change from 2002 to 2017 . In 2017, every state, but New Mexico, has more than 40% of the commercial dairies reporting at least one female core operator. Although these states demonstrate significant increases in the representation of female core operators, the addition of a fourth core operator for the 2017 Census could distort these results.

Consolidation may have allowed dairies to capture improved productivity and efficiency on the farm. How dairy farm size changes in response to these and other factors are important in considering future trends in farm size and their impact on milk production in the United States. My research seeks to help explain recent patterns of farm size change in the dairy industry, considering trends in operator characteristics and management, while accounting for regional differences. The share of women dairy farmers has increased. Historically, farming has been a stereotypically male occupation. Despite contributing to farm production and farm management, surveys, and censuses, have been limited in their collection of data on the contributions of women as farm operators. I hypothesize that some of growth in female contribution to farm operation is due to changes in social and gender norms in reporting. One contribution of my research is to attempt to separate, to the extent possible, changes in management and operations on dairy farms from how such activities are reported. Demographic trends in farm operation and management are important because they help researchers and policy makers get a better sense of who runs the operations in an industry by age, gender, indoor grow cannabis and other characteristics. The dairy industry remains predominately male. However, since 2002, there has been a substantial increase in the share of women dairy farm operators and an increase in the absolute number of dairy farms with at least one female operator in many places.

The share of commercial dairies with at least one female core operator has increased across all states, except New Mexico. New York saw the largest increase in the share of commercial dairies with at least one female core operator from 36% to 55%. California saw a 40% increase in the share of commercial dairies with at least one female core operator. This trend, which has occurred while dairy farm consolidation has proceeded at a similar pace suggests that the participation of female dairy farm operators may positively affect dairy farm herd size and economic viability. As noted in the previous chapter, for the statistical estimation in the thesis I will utilize data for the USDA COA. Under “Census of Agriculture Act of 1997”, The COA is a federally mandated Census of all U.S. farms and ranches every five years, and it captures individual farm-level data on production costs, operators’ characteristics, land use, number of milk cows, revenue, etc. The data and statistics resulting from this Census are reported at the county or state level and research using the individual level data is restricted to USDA research or special request for non-USDA entities. I was given special permission to have access to individual farm-level data for census years of 2002, 2007, 2012, and 2017 from the following specified states: California, Idaho, New Mexico, New York, Texas, and Wisconsin. The National Agricultural Statistics Service , which conducts the Census, attempts to gather responses from every farm in the United States, where a farm is defined as, “is any place from which $1,000 or more of agricultural products were produced and sold, or normally would have been sold, during the census year.” NASS uses a complex sampling procedure that starts with the Census Mail List .

The CML is a mailing list of all potential U.S. farms, as defined by UDSA, The CML is built and improved upon using outside sources, from government lists or different agricultural producer lists. When new names, of potential farms, are discovered they are then treated as a potential farm and added to the CML until the farm is found to not meet the USDA definition of a farm. From there Census data is collected by mail or Computer Assisted Self Interview on the Internet. The respondents submitted one of four different forms: general, short, Hawaii, or American Indian form. The COA data that I use can be described as unbalanced panel data with both attrition and replacement and with occasional errors in recognizing continuing cross-section units. Although the data used is at the individual farm level, no data presented in this thesis reveals any information concerning an individual farm or person. All present research has been subject to a disclosure review and all research using COA data follows the following guidelines, “In keeping with the provisions of Title 7 of the United States Code, no data are published that would disclose information about the operations of an individual farm or ranch. All tabulated data are subjected to an extensive disclosure review prior to publication. Any tabulated item that identifies data reported by a respondent or allows a respondent’s data to be accurately estimated or derived, was suppressed, and coded with a ‘D’. However, the number of farms reporting an item is not considered confidential information and is provided even though other information is withheld.” The survey questions asked of farmers and ranchers by the COA change slightly every Census round, although most questions remain the same across rounds. Below are descriptions of questions changes for relevant variables to the analysis. First, in 2002 and 2007, farms were asked for the total amount of milk or dairy sales in that year, but in 2012 and 2017, this question was dropped and replaced with the total amount of milk sales. Second, operator characteristic questions have become more detailed over the years and allowed more operators to be captured by the Census.

In 2002, 2007, and 2012, the COA asked detailed operator characteristic questions about up to three operators, and only one operator was able to be identified as the principal operator. The COA defined a principal operator as “… the person most responsible for making day-to-day decisions on the farm, during the data collection process.” Whereas an operator is defined as “A farm operator is a person who runs the farm, making day-to-day management decisions. An operator could be an owner, hired manager, cash tenant, share tenant, and/or a partner. If land is rented or worked on shares, the tenant or renter is an operator.” However, in 2017, the COA expanded its detailed operator questions to include up to four operators and now allows for up to four operators to be identified as a principal operator. The definition of principal operator is “Demographic data were collected for up to four producers per farm. Each producer was asked if they were a principal operator or senior partner. A principal operator is a producer who indicated they were a principal operator. There may be multiple principal producers on a farm. Each farm has at least one principal producer.” Whereas operators were defined as “A non-principal is a producer who did not indicate they were a principal operator. There may be no non-principal producers on a farm.” Furthermore, in 2012, curing cannabis the COA started asking farmers and ranchers if the secondary operators were married to the principal operator. This question was then adapted in 2017 to reflect the increase in possible principal operators identified and asked if the operator was married to a principal operator. For our further data analysis, I consider farms that have substantial dairy operations. I want to leave aside those operations that meet the USDA definition of a farm but have minimal connection to commercial dairy production and revenue. To be included as a commercial dairy operation in our sample requires meeting two minimum criteria. First, 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. Second, at least 20 milk cows were on the farm as of December 31 in the Census year. This minimum was set to remove dairy farms that had “exited” and had already removed most of their cow from the farm but still had milk or dairy sales revenue for the year above our minimum criteria. For this research I choose to analyze dairies from six states, California, Idaho, New Mexico, New York, Texas, and Wisconsin. These six states were chosen for my research because they capture the major the U.S. commercial dairy industry and therefore are a useful and representative characterization ofU.S. dairy farming. The following Chapter details the reasoning behind the selection of the six states and characterizing the U.S. dairy industry on the whole. The six states used in this research were selected because they capture a significant share of the U.S. dairy industry and reflect the overall trends. Figure 3.1 shows that these select six states make up the majority share of the total number of milk cows in the United States.

These six states made up almost 55% of total U.S. number of milk cows in 2017 and demonstrated an increasing trend in share of U.S. number of milk cows since the 2002. Figure 3.2 shows that these six states also make up the majority share of milk sales revenue in the United States, with Texas and California making the largest shares in the group. The six states are the leading milk producers in the United States. Although, there are significant differences between each state that I will discuss below, including differences in herd size trends. They represent the majority of the dairy industry, by multiple measures, and they are and representative of national distribution. As discussed in Sumner and Wolf the Eastern states are characterized with many smaller dairies than the other states, including New York and Wisconsin. Whereas, Pacific and Southern states such as, California, Idaho, and New Mexico and Texas , tend to have dairies with larger herd sizes. From 2002 to 2017, California saw a 36% decrease in the number of commercial dairies and a slight larger percentage decrease for farms with milk and/or dairy sales and farms with milk cows. Idaho saw its largest decrease in the number of commercial dairies with farms with milk or dairy sales close behind. However, farms with milk cows only decreased by 20% in Idaho. New Mexico had a very slight 3% increase in the number of farms with milk cows, but a 21% decrease in the number of farms with milk and/or dairy sales and a 26% decrease in the number of commercial dairies. New Mexico saw the smallest percent decrease in commercial dairies from 2002 to 2017 of any of the six select states. New York had about a 50% decrease in the number of commercial dairies and about a 40% decrease in the number of farms with milk cows and farms with milk and/or dairy sales. Texas had the largest percent decrease of across all definitions of dairies. Texas saw a 56% decrease in the number of commercial dairies and 60% decrease in the number of farms with milk and/or dairy sales. Interestingly, there was a 78% decrease in the number of farms with milk cows in Texas which is a significant decrease. Across all three definitions of a dairy Wisconsin had very similar trends with about 46-49% decrease in the number of dairies. In California, there tends to be an increase in larger herd sizes. Figure 3.3 shows the number of farms with milk and/or dairy sales in California for the four Census years and the share of farms with milk or dairy sales by herd size. California saw significant decreases in the smaller herd sizes. Figure 3.4 shows the share of all milk or dairy sales and number of farms with milk or dairy sales by herd size for the state of California. From 2002 to 2017, the share of revenue generated by smaller herd sizes has decreased significantly. The majority of the share of milk or dairy sales revenue has come from dairies with 1,000 or more milk cows and this share has increased to over 80% in 2017. Idaho follows a similar trend as California, Figure 3.5 shows a significant decrease in the smaller herd sizes and growth in the larger herd size groups. Furthermore, between 2002 and 2017 there was significant increase in the share of milk and/or dairy sales from farms with herd sizes greater than 1,000 milk cows . The share of sales revenue from farms with herd size smaller than 499 milk cows fell from about 15% in 2002 to less than 10% in 2017.

Following the farm financial crisis of the 1980s, land prices in the County sharply dropped ; this economic window provided an opportunity for a new generation of farmers to insert a more ecologically-minded approach to farming. Many of these farmers arrived to Yolo County relatively new to farming – often young, educated white urbanites with a desire to farm alternatively to the industrial agribusinesses that had historically dominated the landscape of Yolo County since the early 1900s . Informed by the organic movement, these so-called “back-to-the-land” farmers established innovative, high-value, diversified farms that still exist today. As diversified fruit and vegetable farmers, their approach to farming necessitated learning about and working with their local landscape and ecology . Upon arrival, many were particularly interested in soil fertility and made a conscious effort to avoid “mining the soil” and address ongoing issues with soil degradation in agriculture . While initially these back-to-the-landers lacked historically- and ecologically-specific knowledge of the lands they cultivated , over the last three decades or more, it is highly probable that they have individually amassed a wealth of local, place-based knowledge of their specific management contexts and soil landscapes . To our knowledge, farmer knowledge of local soil landscapes and related soil management practices remains entirely undocumented in Yolo County. Yet, the unique historical and ecological context makes farmer knowledge of soil health and soil management in this region especially important to document; this knowledge is potentially foundational as organic farmers adapt their farming approaches and management in the face of increasing social, economic, vertical grow shelf and environmental uncertainties.

Though many organic farmers in Yolo County are informed by principles of alternative agriculture when managing their soils, it is less clear how these particular farmers have translated their local knowledge of soil into practice and the substance of the soil management practices applied. To address this gap, we used an exploratory approach and examined local farmer knowledge of soil and practical knowledge of soil management in this region. Our objectives were to: 1) Understand how farmers acquire local knowledge of their soils; 2) Document what organic farmers know about their soils; and 3) Determine how these farmers translate this local knowledge into specific management practices related to soil health and on-farm resilience.This research is informed by a Farmer First approach, which recognizes farmers as experts and crucial partners in researching and innovating solutions for resilient, alternative agriculture . The Farmer First approach recognizes multiple knowledge forms and challenges the standard “information transfer” pipeline model that is often applied in research and extension contexts . We used an open-ended, qualitative approach that relies on in-depth and in person interviews to study farmer knowledge. Such methods are complementary to surveys that use quantitative methods for capturing a large sample of responses . Because they are more open-ended, qualitative approaches allow for more unanticipated directions ; however, as Scoones and Thompson point out, removing local knowledge from its local context and attempting to fit it into the constrictive framework of Western scientific rationality is likely to lead to significant errors in interpretation, assimilation, and application.

While interviews are not able to capture the quantity of farmers that surveys do, in-depth interviews allow researchers to access a deeper knowledge base that has inherent value – despite limitations in scalability and/or transferability – as participants respond in their own words, using their own categorization, and perceived associations . Such in-depth interviews are therefore essential to research on farmer knowledge and local knowledge .This research was part of a larger project examining soil health on working organic farms in the region. To identify potential participants for this study, we first consulted the USDA Organic Integrity database and assembled a comprehensive list of all organic farms in the county . Next, with input from the local University of California Cooperative Extension Small and Organic Farms Advisor for Yolo County, we narrowed the list of potential farms by applying several criteria for this study: grow fruit, vegetables, and other diversified crops ; located in Yolo County; at least 10 years of experience in organic farming; and, at least five years of farming on the same land. We chose to focus on diversified fruit and vegetable farmers specifically because of the high demands on soil health and management necessary to farm fruits and vegetables alternatively . We placed minimum limits on farmer experience and time on a particular piece of land in order to ensure farmer knowledge had time to develop; based on an informal survey of farmers throughout California, 10 years was the consensus among these farmers as the amount of time needed to experience aspects of farming “at least once.” This significantly reduced the pool of potential participants; in total, sixteen farms were identified to fit the criteria of this study .Working with a local UCCE advisor helped establish trust with farmers identified. These 16 farmers were contacted with a letter containing information about the study and its scope. Thirteen farmers responded and agreed to participate in the entirety of the study .

These 13 organic farmers represent a majority of the organic farms in the region that grow a diversified array of vegetable and fruit crops and that sell to a variety of consumer markets, including farmers’ markets, wholesale markets, and restaurants. These farmers interviewed also represented 13 individuals who oversaw management and operations on their farms. These individuals were most often the primary owner and operator of the farm, and made key management decisions on their farm.In-person interviews were conducted in the winter, between December 2019 – February 2020; three interviews were conducted in December 2020. We used a two-tiered interview process, where we scheduled an initial field visit and then returned for an in-depth, semi-structured interview. The purpose of the preliminary field visit was to help establish rapport and increase the amount and depth of knowledge farmers shared during the semi-structured interviews. The initial field visit typically lasted one hour and was completed with all 13 participants. Farmers were asked to walk through their farm and talk more generally about their fields, their management practices, and their understanding of the term “soil health.” The field interview also provided an opportunity for open dialogue with farmers regarding management practices and local knowledge . Because local knowledge is often tacit, the field component was beneficial to connect knowledge shared to specific fields and specific practices. After the initial field visits, vertical farming supplies all 13 farmers were contacted to participate in a follow up visit to their farm that consisted of a semi-structured interview followed by a brief survey. The semi-structured interview is the standard technique for gathering local knowledge . These in-depth interviews allowed us to ask the same questions of each farmer so that comparisons between interviews could be made. To develop interview questions for the semi-structured interviews , we established initial topics such as the farmer’s background, farm history, general farm management and soil management approaches. We consulted with two organic farmers to develop final interview questions. The final format of the semi-structured interviews was designed to encourage deep knowledge sharing. For example, the interview questions were structured such that questions revisited topics to allow interviewees to expand on and deepen their answer with each subsequent version of the question. Certain questions attempted to understand farmer perspectives from multiple angles and avoided scientific jargon or frameworks whenever possible. Most questions promoted open ended responses to elicit the full range of possible responses from farmers. In the interviews, we posed questions about the history and background of the participant and their farm operation, how participants learned to farm, and to describe this process of learning in their own words, as well as details about their general management approaches. Farmers were encouraged to share specific stories and observations that related to specific questions. Next, we asked a detailed set of questions about their soil management practices, including specific questions about soil quality and soil fertility on their farm. In this context, soil quality focused on ecological aspects of their soil’s ability to perform key functions for their farm operation ; while soil fertility centered on agronomic aspects of their soils’ ability to sustain nutrients necessary for production agriculture . A brief in-person survey that asked a few demographic questions was administered at the end of the semi-structured interviews. Interviews were conducted in-person, on farms to ensure consistency and to help put farmers at ease.

The interviews typically lasted two hours and were recorded with permission from the interviewee.Interviews were transcribed, reviewed for accuracy, and uploaded to NVivo 12, a software tool used to categorize and organize themes systematically based on research questions . Coding is a commonly used qualitative analysis technique that allows researchers to explore, understand, and compare interviews by tracking specific themes . Through structured analysis of the interview transcripts, we identified key themes and constructed a descriptive codebook to delineate categories of knowledge. Once initial coding was complete, we reviewed quotations related to each code to assess whether the code was accurate. First, we tallied both the number of coded passages regarding different themes or topics, and the number of farmers who addressed each theme. Second, we examined the content of the individual coded entries to understand the nature of farmer knowledge and consensus or divergence among farmer responses for each theme.The following results represent a small window into the collective pool of knowledge from the organic farmers involved in this study, based on their responses to interview questions. Consequently, these results only identify and characterize general types of knowledge that these 13 farmers shared during interviews, but does not fully encompass all types of knowledge that these particular farmers possess. Most importantly, these farmers are not necessarily representative of all organic farmers within their region, or beyond. Where we reference “the farmers” in the sections below, they refer specifically to the farmers in this study, not all farmers. Below, we introduce farmer demographics of this study, situate these farmers’ knowledge in terms of their connection to the land, and also provide insight on how farmers in this study accumulate knowledge; finally, we synthesize key themes that emerged from farmer interviews with regards to soil health and soil management.We interviewed 13 organic farmers, which represents about 80% of certified organic vegetable growers in Yolo County, California who focus on growing diversified crops and have been farming for at least 10 years. Farmer participants were majority white and all either first or second generation settlers in Yolo County, CA. This interview pool included 10 men and 3 women between the ages of 45 to 70. Nearly all farmers had post secondary education. In addition, each farmer interviewed was actively managing their farm at the time of the interview and represented the primary decision maker on the farm. Most of the farmers either grew up on a farm and/or had worked on a farm prior to assuming farm management at their current farm operation. Only three farmers were second generation farmers, and the remainder were first generation farmers. All the farmers had been farming for at least a decade, and most of the farmers had been farming for at least three decades, typically on the same lands. Nearly half of the farmers expressed they were at a big turning point in their personal lives when they decided to farm full time. For example, these farmers had either moved across the country to an unfamiliar place, had quit their office job, and/or had lost an important family member or their childhood home.Farmers interviewed possess embedded knowledge, which is knowledge that comes from living on the land and observing natural processes . To situate this type of knowledge in this particular place , the farmers described their relationship to the land they farmed. Not surprisingly, many of the farmers initially responded with personifications of their land . Initial responses also spoke to farmer perception of their role within the land as well as an expression of romanticism for their land . Among farmers who owned most of the land that they farmed , there was a distinct lack of reference to land ownership; these farmers described their relationship both as a responsibility and as part of a larger human inheritance.

The GBA encompasses bidirectional communication between the central and the enteric nervous systems , linking emotional and cognitive centers of the brain with intestinal functions . The autonomic nervous system, the ENS, and the hypothalamic pituitary adrenal axis mediate the communication of the GBA. Enteroendocrine signaling through enteroendocrine hormones activates neuronal pathways, including extrinsic afferent neurons, sending messages to the CNS. These pathways mediate not only behaviors associated with food intake but also cognition and mood. Cannabis has been associated with significant increases in ghrelin and leptin, and decreases in PYY, consistent with the modulation of appetite hormones mediated through endocannabinoid receptors.61The endocannabinoid system encompasses a key interface between the gut microbiota, the immune system, and homeostasis of the human host. Two main endogenous cannabinoids, or endocannabinoids, are the brain-derived arachidonoyl ethanolamide, known as anandamide , and 2-arachidonoylglycerol derived from lipid precursors, such as arachidonic acid, that are synthesized on demand. 2-AG has been isolated from both gut and brain Thissue. Endocannabinoids in the postsynaptic neuron are released into the synaptic cleft and travel retrograde to the presynaptic neuron, where they inhibit neurotransmitter release; then they are rapidly metabolized by lipoxygenase, cyclooxygenase, and epoxygenases, enzymes involved in eicosanoid metabolism. AEA and 2-AG can also be degraded by hydrolysis into arachidonic acid and glycerol/ethanolamine by serine esterases. The cannabinoid receptors type-1 and -2 are located throughout the periphery and are concentrated in the GI tract.

CB1 receptors are most abundant in the brain, grow tray stand where they function in neurotransmision. The CB1 receptors are predominantly located in the nociceptive areas of the CNS, the cerebellum, hippocampus, limbic system, and the basal ganglia. These receptors have a limited concentration in the substantia nigra and periaqueductal gray matter, but are not observed in the medullary respiratory centers. CB1 receptors can also be expressed on immune, cardiac, and testicular cells. In the GI tract, CB1 agonists are involved in feeding behavior, GI motility, satiety signaling, and energy balance. CB1 peripheral activity includes lipogenesis and inhibition of adiponectin found at elevated levels in obese and diabetic individuals. CB1 signaling has been linked to increased levels of free fatty acids, low HDL, high triglycerides, and insulin resistance. CB2 receptors are expressed mainly on membranes of immune and hematopoietic cells in the periphery. CB2 receptors are densely located in immune Thissue and organs, expressed by diverse cell types, including macrophages, splenocytes, microglial, monocytes, and T cells resident in the thymus, spleen, and bone marrow and tonsils. CB2 receptors located in the periphery have an immunomodulatory function playing an important role in pain reduction, inflammation, and physiological immune defense. CB2 activation mediates a regulatory or suppressive anti-inflammatory effect but in some cases stimulation of CB2 stimulates Thissue destruction and apoptosis, such as in cancer cells. Agonists of this receptor do not have psychoactive properties and are effective in mediating immunosuppression, preventing fibrosis or other organ scarring or in certain diseases triggering Thissue damage.

Antagonistic ligands for the endocannabinoid receptor signaling in the gut have an anti-inflammatory effect with an attenuation of inflammatory cytokines, an increase in Akkermansia muciniphila, and decreases in Lachnospiraceae and Erysipelotrichaceae diversity in the gut. CB1 signaling is TLR4 dependent and known to be influenced by at least A. muciniphila.  In one study, A. muciniphila administration increased the intestinal levels of endocannabinoids that control in- flammation, the gut barrier, and gut peptide secretion. CB1 activation is anti-inflammatory in the gut. The dysbiotic gut environment and GALT are set up for an augmented cycle of inflammation and increased permeability of the gut epithelial barrier. The gut microbiota sends signals to the brain while affecting many functions through several pathways that comprise the GBA, including emotion and cognition . HIV infection may, therefore, lead to the destabilization of the GBA through alterations of the immune system and gut, a possible consequence of ongoing gut epithelial barrier abnormalities and viral replication in the GALT persisting despite ART effectiveness in suppressing peripheral virus. HIV infection and associated gut inflammation disrupt the gut-endocannabinoid-brain interface, and these disturbances adversely affect brain function. While interactions between the gut microbiota and the endocannabinoid system are complex, there are likely to be opportunities to develop therapeutics targeting this axis. Binding of the plant-based cannabinoid THC to presynaptic cannabinoid receptors, in the CNS, principally CB1, mimics the biological properties of AEA, acting like a mood enhancer and stimulant of joy and happiness or euphoria. 

Cannabis administration is associated with significant increases in ghrelin and leptin and decreases in hormones that modulate appetite mediated through endogenous cannabinoid receptors. Medicinal and recreational cannabis comes in at least two species, Cannabis indica and Cannabis sativa, and in a variety of cultivars and formulations with different reported efficacies for treatment of various conditions. ‘‘Cultivar’’ is short for ‘‘cultivated variety’’ and represents not a taxonomic category, but a horticultural one, describing different plants that have been bred and selected by humans . Examples of cultivars include Acapulco Gold and Charlotte’s Web. Acapulco Gold is a golden-leafed C. sativa strain originally from the Acapulco area of southwest Mexico. Charlotte’s Web is a high-CBD, low-THC cannabis variety and extract marketed as a dietary supplement under federal law of the United States. More than 2,000 cultivars are available to consumers, but their chemical constituents and consistency have not been systematically characterized. This highlights the importance of providing consumers with consistent product information. CBD/THC extracts are reported to be more effective at treating pain compared to THC alone both in rodents and in human cancer-related pain. Species and cultivar differences in effects on the microbiome have not been studied. There is also the chemovar referring to the different chemical varieties rather than the strain. Each of the chemovars will have variations in the cannabinoids isolated from the strain in various concentrations of CBD, THC, cannabivarins, CBN, cannabigerol, and other chemicals such as terpenes. Each of them has specific functions and is able to elicit unique pharmacological actions and effects. Modes of administration are also important with respect to effect of cannabis and its therapeutic uses. Whether mode of administration differentially influences the gut microbiome is unknown. For example, one might expect orally administered cannabis to have more potent effects on the gut microbiome given high local concentrations than inhaled cannabis. But this has not been studied. Modes of administration will vary in time to onset of effects. Inhaled versions have a rapid onset of effect based on inhalations, whereas ingestion has a longer time to onset due to the transit to digestive processing and absorption. Finally, it is difficult to ascertain the dosing due to individual effects on physiology and tolerance. The low systemic bio-availability of orally administered cannabinoids has led to exploration of other routes, including intranasal, transdermal, and transmucosal. These are possible because of the highly lipophilic nature of cannabinoids. Additional approaches to formulation that may influence bioavailability include salt formation , co-solvency , micellization , –emulsification, complexation , hydroponic racks and encapsulation in lipid-based formulations and nanoparticles. The U.S. Federal Drug Administration has approved three synthetic cannabinoids and one plant-derived cannabinoid. Marinol is approved for anorexia and nausea related to HIV and chemotherapy; Cesamet is approved to treat chemotherapyinduced nausea and chronic pain; and Epidiolex is a plant-derived CBD indicated for the treatment of seizures associated with Lennox–Gastaut syndrome or Dravet syndrome in patients 2 years of age and older.Emerging findings suggest that cannabinoids can modulate the gut microbiota and inflammatory states by stabilizing blood–brain barrier function and reducing neuroinflammation. Neuroinflammation related to chronic immune activation, oxidative stress, and microbial translocation by a leaky gut barrier could affect the CNS through enteroendocrine signaling and the vagus nerve.

These routes may interact with the better understood link between LPS translocation and chronic in- flammation in the CNS due to microglial activation. Since inflammation and immune activation are believed to contribute to neurocognitive impairment in HIV,  the antioxidant and anti-inflammatory properties and possible effects on gut barrier integrity of cannabinoids may favorably impact neurocognitive function. When THC and other exogenous cannabinoids interact with the endocannabinoid system, they can relieve pain as a result of neuromodulatory actions on both afferent pain signals and brain processing of pain. Several other potential therapeutic interventions have not been rigorously studied in randomized, controlled clinical trials. There is substantial evidence that THC stimulates appetite and reduces nausea. CBD is not psychoactive, acting as a serotonin 5-HT1A receptor agonist, and also has antioxidant and anti-inflammatory properties. In addition, although CBD has a low binding affinity for CB1 and CB2 receptors, it modulates several noncannabinoid receptors and ion channels and delays the ‘‘reuptake’’ of endogenous neurotransmitters such as anandamide and adenosine, by altering the binding of ligands to certain G-protein coupled receptors.Reports suggest that CBD may be effective for managing multiple anxiety based disorders, such as panic attacks, post-traumatic stress disorder, generalized anxiety, obsessive–compulsive disorders, and some cancers. Endocannabinoid signaling is known to influence gut barrier integrity, providing a highly relevant context for the study of the effects of cannabis. The endocannabinoid system in the large intestine interacts with the gut microbiota to regulate epithelial barrier permeability. The endogenous cannabinoid AEA, acting through CB1 and CB2 receptors, plays a pivotal role in maintaining immunological homeostasis and health in the gut. AEA contributes to the process by which the gut immune system actively tolerates microbial antigens. The bioactive lipid agonists and antagonists of cannabinoid receptors are known to have a direct effect on gut barrier function. Some CB1 and CB2 ligands are considered ‘‘gate openers,’’ promoting inflammation due to increased permeability of food antigens and pathogen-associated molecular patterns . Other CB1 and CB2 ligands promote increased barrier function and reduce inflammation. Enteroendocrine L cells are innervated by enteric glial cells and afferent neurons. Enteroendocrine L cells express endocannabinoid receptors . SIV infection was associated with gut epithelial barrier disruption, markers of increased inflammation/ immune activation , disrupting the translational control of IRAK1, and facilitating persistent GI inflammation. Previously published animal model studies support our focus on gut barrier permeability in the context of HIV and cannabis. One study demonstrated that chronic THC was associated with anti-inflammatory Th2 cytokine expression and reduced apoptosis among animals infected with SIV with markers of increased in- flammation and immune activation in epithelial crypt cells. These THC-mediated gut alterations were associated with reduced neuroinflammation measured as lower levels of TNFa, IL1b, IL6, and MCP1 in the striatum of SIV-infected rhesus macaques. These results may possibly translate to PWH; however, there were notable sex-specific differences in THC outcomes in SIV infected macaques. While THC mediated clinical differences in male rhesus macaques, reducing morbidity and mortality, as well as attenuation of SIV disease progression, female macaques did not demonstrate those protective benefits at similar doses. Male rhesus macaques had a reduction in plasma viral levels, decreased expression of Thissue pro-inflammatory cytokines, and a decrease in intestinal apoptosis. Female macaques did not have protective benefits with alterations in SIV viral load and CD4 + /CD8 + ratio, with chronic daily THC administration. These contrasting effects may be due to endocrine hormonal differences, requiring more research to investigate the mechanisms for differences. Given these findings and the numerous studies reviewed and cohorts, the field of HIV-related gut dysbiosis is biased toward males and particularly MSM. Future studies should consider of purposively including adequate sampling of HIV-infected cis-females especially in examining the effects of phytocannabinoids. Recently, studies have determined that cannabis is associated with reduced markers of immune activation and inflammation in CSF. This reduction was based on previous research demonstrating that selective stimulation of CB2 receptor leads to neuroinflammation and microglial activation. Thirty-six PWH and 21 HIV negative participants underwent lumbar puncture and provided estimated days since their last cannabis use . More recent use of cannabis was associated with significantly lower CSF levels of IL-16 and C-reactive protein . These findings are consistent with the notion that CNS anti-inflammatory effects of cannabinoids may be mediated directly through the microglial CB2 receptors or indirectly, for example, through cannabis-mediated alterations in gut microbiota composition, improved gut barrier function, or reduced translocation of proinflammatory bacterial products .Over time, internal and external factors such as prolonged stress, environmental factors, poor nutrition, and overuse of cannabis may influence the ability to produce endocannabinoids. Clinical endocannabinoid defi- ciency syndrome has been linked to migraines, neuromuscular pain, and GI disorders. Specific symptoms and symptom clusters have been linked to a defi- ciency in the endocannabinoids, AEA and 2-AG.

Cultivation of marijuana and the associated use of toxicants have been recently documented in occupied fisher habitat. In addition to the four fisher mortalities attributed to anticoagulant rodenticides by Gabriel et al. , we documented nine additional pesticide toxicosis cases in the present study. The average incidence of toxicosis cases per year for the five year Gabriel et al. study spanning 2007–2011 was 5.6% . However, in the final three years of our study, we detected an increase in incidence per year to 18.7% . Exposure also increased from 79% to 85% for the same two time periods. This increase in cases and exposure could signify either an increase in the number of cultivation sites or area impacted or that cultivators are increasing the level of toxicants being dispersed within occupied fisher home ranges. In either case, this anthropogenic threat is of increasing concern. Previous reports of cholecalciferol poisonings have not been reported in a remote forest dwelling carnivore. This type of toxicant has been promoted as an alternative to anticoagulant rodenticides due to the minimized risk for secondary poisonings. Nevertheless, plant and animal based food flavorizers are often incorporated into rodenticides to enhance palatability to omnivorous rodents. Because fishers are omnivorous, they could be susceptible to primary poisoning if they are attracted to these compounds when they are impregnated with flavorizers. In addition, the massive amount of rodenticide dispersed at some cultivation sites e.g>40 kg in some sites, rolling grow table which have cultivation footprints of typically less than 0.2ha likely pose a secondary risk of poisoning to fishers. Fishers may consume numerous prey that may have recently ingested these rodenticides, with the likely exception of cholecalciferol.

As was noted previously for a subset of cases, toxicosis deaths occurred primarily in the spring. Additionally, males were more likely than females to die of poisoning relative to predation and other causes. This finding may be due to fewer predation events involving males than females or the higher prevalence of poison-related mortality in males. These trends could also be due to behavioral factors. Female fishers in California increase their crepuscular and diurnal activity in spring to saThisfy the additional energy requirements of lactation and care of weaned kits but typically within the confines of their established home-ranges. Male fishers may make extensive forays outside their normal home ranges in spring to search out females for mating opportunities. Marijuana cultivation coincides with the increased activity of fishers in early spring and frequently involves dispersal of large amounts of toxicants near occupied fisher home ranges. Furthermore, survival of female fishers in one population was found to be influenced by the number of marijuana cultivation sites in the 95% fixed kernel home range. The relationship between the number of ARs to which a fisher has been exposed and the increasing probability of death due to poisoning suggests that these pesticides may be acting additively or synergistically. However, little experimental data are available demonstrating exposure to multiple ARs increasing the risk of coagulopathy. Our data suggest that coagulopathy risk increases significantly with each additional new AR compound exposure, though it’s possible this pattern is reflecting an additive relationship between AR number and cumulative level of exposure. However, potential synergistic mechanisms need to be addressed due to the significant amount of other pesticides, herbicides, molluscicides and fungicides documented at marijuana cultivation sites. Because fishers are exposed to > 1.7 different ARs on average, our concerns on the potential unknown mechanisms of deleterious effects of multiple ARs warrants further investigation.

Human-related mortalities were relatively rare, and although a small number were associated with research activities, such mortalities represented < 1% of the captured fishers. This figure is comparable to other studies. Vehicle-related mortalities were also relatively rare with only three marked fishers suffering vehicle strikes, which represented < 2% of all mortalities. The higher number of uncollared fishers found killed in roadways suggests that roadkill may be a more local concern, associated with individual high-traffic corridors. Field biologists did not always accurately identify general causes of disease. We found only a moderate correspondence between biologist-determined and necropsy-confirmed causes of death except for the detection of disease-related mortalities, which were significantly underestimated by initial field assessments. For example, the three fisher deaths attributed to CDV and many of the toxicosis cases were preliminarily attributed to other causes in the field. The underestimation of disease has been observed in other wildlife studies because gross observations in the field are inadequate to detect subtle signs of disease. These findings fortify the need for full necropsies when studying causes of mortality, especially when knowledge of the frequencies of cause-specific mortality is required in managing or reducing the most significant limiting factors for fishers. Although predation was often correctly identified by both field biologists and the pathologists, the incorporation of molecular forensic approaches coupled with traditional pathology allowed us to more definitively identify both predation events and predator species. Predation is often implicated as the cause of mortality when field evidence such as tracks near or adjacent to the carcass, bite wounds, wound patterns or feces and/or hair near the carcass are found. However in our study, field observations misclassified 5 fishers as predation due to circumstantial predator evidence found near the carcass .

Field observations can be misleading, for example, bite wounds in soft Thissue often change shape and size due to environmental factors and visual artifacts that resemble ante-mortem hemorrhaging can occur due to autolysis, scavengers consuming Thissue and releasing non-clotted blood, or freezing and defrosting of a carcass. Finally, we present mainly the proximate causes of mortality for fishers though there were a few cases where ultimate causes could be ascertained e.g. anesthesia related death but clinically infected with CDV. However, it would be difficult, if not impossible, to determine whether some of the predation mortalities were ultimately going to result in toxicosis. Many of the predation cases exhibited ante-mortem hemorrhaging that could have been due directly to predation or alternatively, AR exposure. Anticoagulant rodenticides have previously been shown to cause lethargy and weakness in exposed animals, but teasing these two causes of death apart was not possible. This study presents the first large assessment of cause-specific mortality frequencies in California fishers. We have identified predation and natural disease as the top two mortality factors. In addition, mortality from and exposure to toxicants appears to be on the rise and we have found exposure to multiple ARs increases probability of death from these compounds. Increases of additive mortality of only 10% can prevent fisher population expansion even in the presence of suitable habitat with no dispersal barriers. Therefore, the high proportion of fisher mortality consisting of predation and disease may help explain the lack of growth and expansion of these populations to nearby suitable habitat. However, the growing number of toxicosis cases in fishers and the correlation of contributing mechanisms such as marijuana cultivation within fisher habitat suggest an emerging threat. Beyond direct poisoning, rodenticides have the potential to limit fitness through prey depletion and heightened competition between fishers and other carnivores. Future research should focus on the relationship between marijuana cultivation and associated rodenticide use and prey population cycles because carnivore population dynamics are often heavily influenced by fluctuations in prey base. Managing these threats should focus not only on the impacts on current fisher populations but also the reduction of threats that may be limiting expansion for future population growth. One recommendation is the complete removal of toxicants left at current and historicaltrespass marijuana grow sites. Most sites are not remediated, indoor plant table thus toxicants associated with these sites are a continuing threat. Furthermore, as female adult survival is notably important for population size and persistence in the southern Sierra Nevada population, forest managers should consider managing against habitat features that are conducive to interactions between fishers and their predators. Investigating these and other mechanisms for reducing mortality in California fishers within West coast DPS can be of assistance in effectively implementing policy or management options to potentially curb mortality rates in order to promote population recovery within California in addition to other fisher populations throughout the West Coast DPS.We would like to acknowledge the contributions of the following people and organizations. University of California at Davis Veterinary Medical Teaching Hospital, the graduate group of Comparative Pathology, Drs. Jonna Mazet, the field biologists at all the projects sites. Integral Ecology Research Center, California Animal Health and Food Safety Laboratory System, Hoopa Valley Tribal Forestry, United States Forest Service, National Park Service, United States Fish and Wildlife Service, California Department of Water Resources, California Department of Fish and Wildlife, California Department of Forestry and Fire Protection, and the Sierra Nevada Conservancy, and the Bureau of Indian Affairs provided logistical support.

We would like to thank two anonymous reviewers for making notable suggestions that improved the manuscript. Most of all we would like to thank the late Dr. Linda Munson forinitially taking the fisher health project under her wing. Her mentorship and contributions to wildlife conservation will be remembered and appreciated.Cannabis is one of the most frequently used psychoactive substances in the world and is the subject of major debates between proponents of the gateway hypothesis and advocates of legalization. Proponents of the gateway hypothesis have argued that epidemiological studies indicate that the early use of cannabis is an important risk factor for initiating cocaine use, that cannabis dependence predicts cocaine dependence , that cannabis use may be associated with poor cognitive and psychiatric outcomes in adulthood , and that major changes in legalization of the possession, sale, and cultivation of cannabis in the United States may exacerbate these poor outcomes by increasing the level of cannabis use in adolescents and young adults. Currently, its use exceeds that of tobacco smoking among adolescents in the United States, in which 37.1% of high school seniors in 2017 reported using cannabis within the past year. Advocates of legalization and medicinal use argue that it is unclear whether the relationship between prior cannabis use and later cocaine use or cocaine use disorder is caused by cannabis use per se or other drug-associated factors, such as concomitant psychiatric disorders and socioeconomic status. However, epidemiological studies cannot establish causal relationships between the pharmacological effects of exposure to cannabis and the development of cocaine use. Preclinical studies provide a controlled way to study causal relationships between early-life cannabinoid exposure and cocaine use, including compulsive-like use, later in life. Previous studies reported that exposure to the cannabinoid receptor agonist WIN55,212-2 during adolescence decreased the reactivity of dopaminergic neurons to WIN , produced cross-tolerance to cocaine in adolescence, and produced cross-sensitization to the psychomotor effects of cocaine in adolescence but not in adulthood. This effect appears to be mediated by the modulation of eukaryotic initiation factors in the brain. Such modifications of key neural substrates may reprogram the adolescent brain and make it more susceptible to the later use of other illicit drugs, such as cocaine. However, other groups found that prior treatment with either the main psychoactive constituent of cannabis or WIN had no effect on behavioral responses to amphetamine in either adolescence or adulthood. However, in the study by Ellgren et al. , cannabinoid exposure lasted only 5 days, the doses of cannabinoid were low, and the animals were injected only once per day. A major limitation of these preclinical studies is the use of an animal model of cocaine exposure that reflects neither the direct acquisition of cocaine use nor the compulsive nature of cocaine use disorder . To address this issue, we tested the effect of adolescent exposure to the cannabinoid receptor agonist WIN on key addiction-related behaviors using a more complex animal model of drug addiction. The model included measures of irritability-like behavior, which has recently been used as a measure of the negative emotional state in animal models of addiction. We also assessed cocaine-induced locomotion in adolescence and adulthood and the acquisition of cocaine self-administration under conditions of short access and long access in adulthood. The long-access model represents a comprehensive model of human addiction because it produces the escalation of cocaine intake that is associated with the emergence of negative emotional states and compulsive-like responding despite adverse consequence.All behavioral testing was conducted during the dark phase.

Since AIDS patients are treated with anti-retroviral therapies, researchers explored the potential impact of cannabinoids on indinavir and nelfinavir and found no significant impact of marijuana on the efficacy of these drugs . The first written account of medicinal marijuana took place in China in the 5th century BC , and with ongoing research of cannabinoid receptors and endocannabinoids, the therapeutic actions of marijuana are becoming clearer. Medicinal marijuana has been a controversial topic for many years which is characterized by the petition in the 1970s to convert marijuana from a schedule I drug to a schedule II drug and the support of rescheduling and appeal by the Drug Enforcement agency in the 1980s . In 1996, California proposition 215, the Compassionate Use Act, passed and stated “Patients and caregivers may possess or cultivate medical marijuana for medical treatment” . This vague statement that legalized marijuana enraged the government and health care providers because of the new stereotypes regarding the safety of marijuana and the lack of regulation. As a result, the federal government attempted to eliminate medicinal marijuana indirectly by prohibiting physicians to discuss medicinal marijuana with the consequence of losing prescription writing privileges . In addition, the definition of pharmaceutical grade marijuana and its production has been an area of active debate. The heterogeneous population of medicinal marijuana fails to meet a consistent standard of composition and quality . Solving this problem would require pharmaceutical companies to successfully develop a synthetic cannabinoid derivative .

In the modern patient-centered health care system, cannabis growing system health care providers must acknowledge the current research and make evidence based decisions on the benefits of medicinal marijuana as a treatment for cancer and AIDS related weight loss. Fifteen years ago, the existence of cannabinoid receptors was unknown, but research has painted a clearer picture of the hypothalamic CB1 receptors’ role in appetite stimulation. Despite the controversy of medicinal marijuana, continued research in this field has opened new avenues for treatment and prevention of the nation’s biggest health care problem, obesity. Understanding the cannabinoid receptors’ role in appetite suppression and its link in the leptin pathway may allow future physicians to treat and prevent obesity . Obesity is a significant risk factor for deadly diseases such as atherosclerosis, hypertension, and diabetes, and further research in medicinal marijuana’s role in appetite stimulation may be the key to curing an obese nation. Although the amount of information regarding medicinal marijuana is vast, there are many areas that need further research for more effective use among patients. First, double blind randomized control trials in humans are needed to truly assess the effectiveness of marijuana in appetite stimulation. Many studies on rats and mice have produced a working scientific basis for medicinal marijuana, but human trials are necessary to assess potential benefits and adverse effects in patients. Further, a risk/benefit analysis of medicinal marijuana is needed. Medicinal marijuana is often disputed as a treatment based on its side effect profile, but terminally ill cancer and AIDS patients might be willing to increase their risk for lung cancer in the long term to achieve an immediate improvement in quality of life. With a target population of immuno compromised patients, research on alternative delivery methods need to be employed to decrease the risk of infection associated with marijuana smoking.

Finally, a logistical study on the most effective and safest mechanism for distribution of marijuana in the population must be conducted. With this information, marijuana can be utilized safely to allow sick patients to engage in one of the most essential actions in life, eating. With the passage of Proposition 64 , state voters elected to integrate cannabis into civil regulation. Prior to the possibility of state licensure for cultivators, however, counties can decide on other designations and implement strict limitations. In effect, local governments have become gatekeepers to whether and how cultivation of personal, medical or recreational cannabis can occur and the repercussions of noncompliance. When cannabis is denied a consistent status as agriculture, despite being a legal agricultural commodity according to the state, localities can determine who counts as a farmer and who is considered compliant, non-compliant and even criminal. In Siskiyou County’s unincorporated areas, the Sheriff’s Office now arbitrates between the effectively criminal and agricultural. Paradoxically for this libertarian county, the furor around cannabis has seen calls for government intervention, and has led to officials passing highly stringent cannabis cultivation regulations that have been enforced largely by law enforcement, muddying the line between noncompliance and criminality. These strict regulations produced a situation where “not one person” has been able to come into compliance, according to a knowledgeable government official. Nonetheless, at the sheriff’s urging, Siskiyou declared a “state of emergency” due to “nearly universal non-compliance” , branding cannabis cultivation an “out-of-control problem.” Such a strong reaction against cannabis can be understood in terms of cannabis’s potential to reorganize Siskiyou’s agricultural and economic landscape. According to some estimates, there are now approximately twice as many cannabis cultivators as non-cannabis farmers and ranchers in Siskiyou , a significant change from just a few years ago. Although cannabis has been cultivated in this mostly white county for decades, since 2015 it has become associated with an in-migration of Hmong-American cultivators. 

Made highly visible through enforcement practices, policy forums and media discourses, Hmong-Americans have become symbolically representative of the “problem.” This high visibility, however, obscures a deeper issue, what Doremus et al. see as a nostalgic, static conception of rural culture that requires defensive action as a bulwark against change. Such locally-defined conceptions need to be understood , especially in how they are defined and defended and what effects they have on parity among farmers growing different types of crops. Our goals in this study were to consider the consequences of an enforcement-first regulatory approach — a common regulatory strategy across California — and its differential effects across local populations. Using Siskiyou County as a case study, we paid attention to the public agencies, actors and discourses that guided the formation and enforcement of restrictive cannabis cultivation regulations as well as attempts to ameliorate perceptions of racialized enforcement. This study attends to novel post legalization apparatuses, their grounding in traditional definitions of culture and the ways these dynamics reactivate prohibition. We used qualitative ethnographic methods of research, including participant observation and interviews. In situations of criminalization, which we define not only as the leveling of criminal sanctions but being discursively labeled or responded to as criminal-like , quantitative data can be unreliable and opaque, which necessitates the use of qualitative ethnographic methods . In 2018–2019, we talked to a wide range of people — including cannabis growers from a diversity of ethnic backgrounds, government officials, business people, subdivision residents, farm service providers, medical cannabis advocates, realtors, lawyers, farmers and ranchers, and, with the assistance of a Hmong-American interpreter, members of the Hmong-American community. We also analyzed public records and county ordinances, Board of Supervisors meeting minutes and audio , Sheriff’s Office press releases and documents, related media articles and videos, flood table and websites of owners’ associations in the subdivisions where cannabis law enforcement efforts have focused. Some cannabis cultivators regarded us suspiciously and were hesitant to speak openly, an unsurprising phenomenon when researching hidden, illegal and stigmatized activities, like “drug” commerce . This circumspection was most intense among Hmong-American growers on subdivisions, who had been particularly highlighted through enforcement efforts and local, regional and national media accounts linking their relatively recent presence in Siskiyou to cannabis growing. Human subjects in this research are protected under the Committee for Protection of Human Subjects, protocol number 2018-04-1136 , of the Office for Protection of Human Subjects at UC Berkeley.Siskiyou is a large rural county located in the mid-Klamath River basin in Northern California . Since the mid-19th century, in migrants have historically engaged in agriculture, predominantly livestock grazing and hay production, and natural resource extraction, primarily timber and mining . Public records demonstrate that although the value of the county’s agricultural output and natural resource extraction is declining, these cultural livelihoods still shape the area’s dominant rural values of self-reliance, hard work and property rights .

For instance, one county document stated that Siskiyou’s cultural-economic stability depends on nonintervention from “outside groups and governments” and residents should be “subject only to the rule of nature and free markets” . Another document, a “Primer for living in Siskiyou County” from the county administrator, outlined “the Code of the West” for “newcomers,” asserting that locals are “rugged individuals” who live “outside city limits,” and that the “right to be rural” protects and prioritizes working agricultural land for “economic purpose[s]” . We heard a common refrain that localities will eventually succumb to the allure of a taxable, profitable cannabis industry. Indeed, interviewees in Siskiyou universally reported economic contributions from cannabis cultivation, especially apparent in rising property values and tax rolls and booming business at horticultural, farm supply, soil, generator, food and hardware stores . However, a belief in an inevitable free market economic rationality may underestimate the deep cultural logics that have historically superseded economic gains in regional resource conflicts . As one local store owner told us, “I’d give up this new profit in a heartbeat for the benefit of our society.” Many long-time farming and ranching families remain committed to agricultural livelihoods for cultural reasons , even as the economic viability of family farms is threatened by increasing farmland financialization , corporate consolidation and biophysical decline . Many interviewees felt that the recent rapid expansion of county cannabis cultivation and corresponding demographic changes were a visible marker of broader tensions of cultural continuity and endangerment. As the sheriff expressed, cannabis cultivation would “jeopardize our way of life … [and] the future of our children” . This sense of cultural jeopardy , echoed by numerous interviewees, materialized in a range of negative quality-of-life comments about cannabis cultivation: noisy generators, increased traffic, litter and blighted properties, and unsafe conditions for residents. Non-cannabis farmers also reported farm equipment and water theft, livestock killed by abandoned dogs, wildfire danger, illicit chemical use and poisoned wildlife. Some non-cannabis farmers expressed a sense of regulatory unfairness — that their farms were subject to onerous water and chemical use regulations while cannabis growers “don’t need to follow the government’s regulations.” Enabling cannabis cultivators to pursue state licensure would facilitate just such civil regulation, but some feared that regulating this crop as agriculture would threaten “the loss of prime agriculturally productive lands for traditional pursuits” . If nothing less than the county’s culture and agricultural order were considered at stake, it is no wonder that absolute, even prohibitionist, solutions emerged in Siskiyou, with the Sheriff’s Office having a central role in defending local culture.Siskiyou’s sparsely populated landscape has been home to illegalized cannabis cultivators at least since the late 1960s, largely in remote, forested, and public lands in the western part of the county. Medical cannabis’s decriminalization in 1996 inaugurated a modest expansion of cannabis gardens throughout the county . However, for the next 19 years, Siskiyou did not establish regulations for medical cannabis, in line with locally dominant ideologies of personal freedoms and property rights. Instead, the county relied on de facto management of cultivation by law enforcement and the court system’s strict interpretation of state law . In 2015, informed by public workshops held by the Siskiyou County Planning Division, supervisors passed the county’s first medical cannabis ordinance, which seemingly balanced concerns of medical cultivators and other county residents. Regulation would be overseen by the Planning Division, which placed conditions on cultivation , limited plant numbers to parcel size and would establish an administrative abatement and hearing process for complaints. The Planning Division, however, had been without code enforcement officers since 2008 budget cuts. Though the county authorized the hiring of one civil code officer in 2015, the Sheriff’s Office felt that the Planning Division “needed outside help” and moved to assist. Soon, the county’s limited abatement capacities were overwhelmed by vigorous enforcement and a wave of complainants. County supervisors, responding to the sheriff’s 2015 reports on the “proliferation” of cannabis gardens on private property, moved to heighten penalties for code violations, place numerous new restrictions on indoor growing and ban all outdoor growing .

By bringing actors from the black market to the taxed and licensed marketplace, the state can raise billions in annual tax revenue and create jobs for thousands of people. The economic justification of cannabis legalization was compelling: if people were going to use it anyway, why not tax it? Other important arguments favoring full legalization were: reducing law enforcement and incarceration costs; alleviation of the drug war in Mexico; breaking with racial disparity of the war on drugs; consumers’ protection through quality control and regulation; defense of individual rights and freedoms; and so forth. The legalization of recreational cannabis is a nascent field of study, which has more questions than answers. Today, it looks that the economic framework has been most influential in the recreational cannabis campaign. With this project, I intend to shed some light on how the legalization of recreational cannabis became possible in California and which frameworks contributed the most to legal change. To answer these questions, I interview people who have a direct bearing on the institutionalization of the idea of recreational cannabis at the local level, i.e., licensed and unlicensed cannabis growers and distributors, social activists, city officials, representative of licensing agencies, and law enforcers. Today, cannabis is the transitional period characterized by a search for a new legitimate meaning. According to Victor Turner, a liminal stage means being “at once no longer classified and not yet classified” . In the case of cannabis, it means that it is no longer illegal but not yet legal; no longer criminalized but not yet legalized; no longer intolerable but not yet entirely acceptable. As cannabis consumption slowly and tentatively gains legitimacy, it also shows some harbingers of its institutionalization.

The binary rhetoric on cannabis—i.e., the medical and recreational perspectives—reflects a lack of a dominant narrative about it . For example, weed trimming tray many physicians do not have a consolidated perspective on whether cannabis is a medicine or not. On the one hand, they want to abide by professional norms and exclude dubious substances from clinical practice; on the other hand, they want to help patients by relieving their pain and suffering . A similar ambivalence exists on the regulatory level. California’s cities have discretion over whether to permit recreational cannabis, and many are still debating what to do. Thus, even if recreational cannabis became legal in some parts of California, it remained illegal in others, as well as on federal property. The persistence of the black market is yet another marker of ambiguity: due to high taxation, many cannabis providers choose not to obtain a license and remain in a shadow area. The socially uncertain state of cannabis partly arises out of its lasting conceptualization as a criminal justice issue. The federal prohibition of cannabis continues to jeopardize the position of every person involved in its cultivation and distribution in California. On December 2, 2020, the United Nations Commission on Narcotics removed cannabis from the list of most dangerous drugs. Two days later, the US House of Representatives approved the MORE Act , which should decriminalize cannabis at the federal level and remove it from the list of controlled substances. Both legislations are important symbolic gestures, but the future of cannabis in the US remains unclear. The federal enforcement agencies are not yet ready to accept cannabis legalization, and sometimes one step forward leads to two steps back. Although the recognition of medical benefits of cannabis use is more widespread now than decades ago, cannabis abuse is rarely perceived as a public health issue . All psychoactive substances that alter physical and mental processes in the human body require a special system of control, and cannabis is not an exception.

The question is: Which social institutions should be responsible for regulating cannabis? In different countries, cannabis sale, use, and abuse is regulated by the healthcare system, welfare institutions, religion, law enforcement, or the market. In the current US context, it comes under the jurisdiction of law enforcement agencies and courts and is viewed from a bureaucratic rather than a professional logic. Federal prohibition of cannabis encourages social stereotypes and impedes ideational change, which is necessary for moving cannabis from criminal justice to the medical, commercial, or recreational discourse. Drug testing in workplaces, widespread anti-cannabis campaigns, the concentration of dispensaries in marginal zones, the stigmatization of cannabis users, the unavailability of banking and legal services, the prohibition of interstate trade, and, of course, the federal prosecution—all these points indicate the heavy symbolic load attached to cannabis use, which means that cannabis is far from being normalized and institutionalized in California. Based on this information, some people might question whether the passage of Proposition, which legalized cannabis for recreational use, was premature. In this project, I argue that the adoption of formal regulation is only one in an ongoing series of episodes contributing to a broader cultural transformation. Asking whether the legalization of cannabis was premature is not relevant if we understand legalization as a process of gradual, incremental change. Such an approach allows us to see how the idea of cannabis is historically constructed through social interactions, strategic political decisions, adaptations, innovations, or even unintended consequences. It also provides a perspective on particularities and paradoxes of public morality, or, better to say, a moral background of contemporary American society . The increased tolerance of cannabis use, which we observe in recent decades, is often referred to as “normalization.” Saying that cannabis is becoming normalized means that the substance is available and accessible, consumption rates are increasing, and that there is greater social and cultural accommodation of its use . Since the 1990s, cannabis had undergone a significant transformation in public perception.

The perceived risk of cannabis is decreasing, along with the cultural anxiety and negative labels attached to it, and its users are less inclined to guard information about their consumption . The tone of media coverage of cannabis-related issues also becomes more favorable . Opinion polls detect broader acceptance of cannabis use: according to Gallup, the support of cannabis legalization grew from 12% in 1969 to 68% in 2020 . Many Americans believe that smoking cannabis is morally acceptable . In 1969, only 4% of Americans said they had tried cannabis; in 2017, that figure grew to 45%. The rates of cannabis and tobacco consumption rose at a similar pace ; however, among young adults aged 18 to 29, cannabis is significantly more popular than tobacco . Availability and access to legal cannabis are also growing: as of December 2020, the recreational use of cannabis is permitted in 15 states and its medical use in 36 states. Yet, despite broader social tolerance, the cannabis issue remains controversial. First, its continuing federal illegality poses a threat of legal sanctions on those using or distributing cannabis under state law. As Sam Kamin points out, “legalized” cannabis continues to operate in an unstable gray area. When the commodity is prohibited at the federal level and legalized at the local level, there might be considerable confusion regarding how governmental, market, educational, cannabis grow setup and other institutions should treat it . In particular, what the true dangers of cannabis use are and how to effectively distribute institutional resources to address these dangers . People engaged in cannabis activity still risk losing their jobs, parental rights, and many federal benefits . For example, the Drug-Free Workplace Act of 1988 requires employers who are federal contractors to maintain a drug-free workplace and prohibits the use and possession of illegal substances. Because the federal government classifies cannabis as an illegal drug, employers in California feel incentivized to impose drug testing at the workplace to comply with the law, even though the Act neither directly demands nor authorizes it . As of now, the attempts to challenge the discriminatory policies against employees using cannabis for medical purposes have been unsuccessful.Second, cannabis users continue experiencing stigma and social disapproval. Many studies show that notwithstanding the normalizing trends, cannabis-related stigma is conspicuous and strongly affects cannabis users’ identity formation . That cannabis is no longer “deviant”—at least in some social circles—does not make it “normal” either . Cannabis users employ various strategies to distance themselves from labels and familiar stereotypes about cannabis use and its relation to crime, deviance, sickness, etc. . Since the 1960s, civil rights movements are fighting for the “normalization” of cannabis use under the banner of recognition of dignity and pride within difference . Despite widespread tolerance and the success of the legalization movement, cannabis use still challenges the dominant values and remains on the margins of the mainstream culture. In 2019, 86% of cannabis supporters believed that cannabis helps people who use it for medical reasons, and only 35% agreed that cannabis use is not harmful. Moreover, cannabis use has potential social consequences—from disapproval by family members to termination of a labor contract.

This project instead underscores the importance of organizationalstigma by bringing attention to actors who are involved in cannabis legalization at the level of practice. I argue that normalization happens not only through changes in public morality and consumption practices but also through establishing new institutions and new social relationships. For example, the legalization of recreational cannabis brought about a variety of new organizational forms, such as licensing agencies, recreational cannabis dispensaries, microbusinesses, testing labs, cannabis cafes and restaurants, cannabis law firms, and so on. These institutions gave rise to new relationships—between cannabis companies and licensing agencies, landlords, law enforcers, lawyers, local communities, or consumers. Like individuals, organizations, or whole markets can also experience stigma, which forces them to exist in the shadows. The passage of Proposition 64 did not put cannabis on a par with other legitimate and tolerated intoxicants . Instead, it placed the emerging legal cannabis market abreast of other markets of morally questionable goods, for which attaining legitimacy is a crucial and pressing issue . For example, while alcohol can be enjoyed at bars, restaurants, or sporting events, there is no public place to consume cannabis lawfully . Moreover, due to incompatibility between state and federal legislation, cannabis companies do not have access to professional services necessary for businesses to function. Banks, attorneys, insurance companies, potential investors, and others are concerned with breaking federal law. As a result, the cannabis market is a cash-based trade that needs enhanced security services . Similarly, landlords are reluctant to let their properties to cannabis operations due to the risk of federal seizures . Since the traditional professions are cautious about engaging with legal cannabis, a pool of “special” cannabis doctors, creditors, and attorneys has emerged. These specialists are often considered marginal within their professional groups. Cannabis dispensaries manage the effect of industry stigma by dismantling the harmful stereotypes and distancing from the “black” market. In particular, they incorporate the language, symbols, and values associated with the healthcare system ; promote themselves as responsible and caring providers ; craft their professional image as experts in pain and anxiety ; imitate normal businesses ; deemphasize potential dangers of cannabis use ; and so on. Despite these efforts, the cannabis industry is not yet fully destigmatized. How can we quantify the current stigma of the legal cannabis industry and understand the extent to which it has been removed? Different theoretical perspectives can give a clue on how to test the normalization hypothesis and measure the effect of organizational stigma. In The Rules of Sociological Method , Emile Durkheim makes a distinction between normal and pathological based on how often individuals encounter different kinds of events. In other words, the criterion of frequency determines whether we call a phenomenon “normal” or “pathological”: normal things are the ones more widespread and common to find. Currently, only one-third of California cities allow cannabis-related activities within their borders, and therefore we can infer that cannabis companies are still a pathology rather than a staThistical norm. Durkheim’s main vulnerability is his disinterest in the social agents’ perspective and the systematic neglect of power . There are many rare social facts, but some become pathological based due to their infrequency, and others do not. Why is that so? To tailor the Durkheimian theory and make it more suitable for my empirical analysis, I incorporate Mary Douglas’s idea of pollution and power.