Since the 1980s, the U.S. Forest Service (USFS) has transformed from an agency predominantly focused on timber production to one focused on recreation and ecosystem management. This shift is particularly remarkable because it occurred without major substantive national forest policy changes. During this period, many national forests changed their forest planning processes in ways that provided greater opportunity for public input into forest plans, and in 2012 the USFS issued new planning rules that institutionalized these practices. In this study, we ask: how has the planning process changed over time, and how have these changes shaped forest plan outcomes? To answer these questions, we conduct a comparative case study of two national forests—the Lake Tahoe Basin Management Unit and the Inyo National Forest—that produced forest plans in the 1980s and again in the 2010s. We use the Network of Action Situations (NAS) approach to compare planning processes over time and across forests. We find that in addition to the changes mandated by the 2012 rules, both forests developed a series of forums to engage the public in plan development and review, and that increased stakeholder engagement has helped shape forest priorities. These findings suggest that greater involvement by regional stakeholders could pressure the USFS to adopt more regional approaches for addressing challenges like climate change and wildfire risk.
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Prosecutors, court communities, and policy change: The impact of internal DOJ reforms on federal prosecutorial practices*
The current study examines how key internal U.S. Department of Justice (DOJ) policy changes have been translated into front-line prosecutorial practices. Extending courts-as-communities scholarship and research on policy implementation practices, we use U.S. Sentencing Commission data from 2004 to 2019 to model outcomes for several measures of prose- cutorial discretion in federal drug trafficking cases, including the use of mandatory minimum charges and prosecutor-endorsed departures, to test the impact of the policy changes on case processing outcomes. We contrast prosecutorial measures with measures that are more impervious to discretionary manipulation, such as criminal history, and those that represent judicial and blended discretion, including judicial departures and final sentence lengths. We find a significant effect of the policy reforms on how prosecutorial tools are used across DOJ policy periods, and we find variation across districts as a function of contextual conditions, consistent with the court communities literature. We also find that a powerful driver of changes in pros- ecutorial practices during our most recent period is the confirmation of individual Trump-appointed U.S. Attorneys at the district level, suggesting an important theoretical place for midlevel actors in policy translation and implementation.
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- Award ID(s):
- 1849089
- NSF-PAR ID:
- 10225095
- Date Published:
- Journal Name:
- Criminology
- Volume:
- 59
- ISSN:
- 0011-1384
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Most studies of policy entrepreneurship seek to understand how entrepreneurs influence the behavior of policy‐makers in the agenda‐setting or decision‐making phases of the policy process. Recent scholarship has sought to understand what role entrepreneurs might play in policy implementation by focusing on their ability to influence bureaucrats' discretion and behavior. However, these studies overlook the potentially critical influence of policy entrepreneurs during the implementation of “opt‐in” policies that require voluntary compliance by individuals to be successful. Here, we consider whether and how a visible policy entrepreneur can impact opt‐in policy implementation, focusing on their credibility—or ability to gain public trust—as a potential driving factor of their influence. Using the empirical context of COVID‐19 vaccination recommendations, we identify Dr. Anthony Fauci as a highly visible policy entrepreneur and assess his influence on individual vaccine intention and uptake. Drawing on data from a novel panel survey of the American public on attitudes about the virus, risk, politics, and vaccination during the first several months of the COVID‐19 vaccine rollout in the United States, we test the relationship between respondent trust in Dr. Fauci and changes in reported intention to vaccinate and vaccination uptake across time. We find that trust in Dr. Fauci is an important predictor for influencing individuals' intention to vaccinate and actual vaccination behavior.
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Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a communicable disease spread through close contact. It is known to disproportionately impact certain communities due to both biological susceptibility and inequitable exposure. In this study, we investigate the most important health, social, and environmental factors impacting the early phases (before July, 2020) of per capita COVID-19 transmission and per capita all-cause mortality in US counties. We aggregate county-level physical and mental health, environmental pollution, access to health care, demographic characteristics, vulnerable population scores, and other epidemiological data to create a large feature set to analyze per capita COVID-19 outcomes. Because of the high-dimensionality, multicollinearity, and unknown interactions of the data, we use ensemble machine learning and marginal prediction methods to identify the most salient factors associated with several COVID-19 outbreak measure. Our variable importance results show that measures of ethnicity, public transportation and preventable diseases are the strongest predictors for both per capita COVID-19 incidence and mortality. Specifically, the CDC measures for minority populations, CDC measures for limited English, and proportion of Black- and/or African-American individuals in a county were the most important features for per capita COVID-19 cases within a month after the pandemic started in a county and also at the latest date examined. For per capita all-cause mortality at day 100 and total to date, we find that public transportation use and proportion of Black- and/or African-American individuals in a county are the strongest predictors. The methods predict that, keeping all other factors fixed, a 10% increase in public transportation use, all other factors remaining fixed at the observed values, is associated with increases mortality at day 100 of 2012 individuals (95% CI [1972, 2356]) and likewise a 10% increase in the proportion of Black- and/or African-American individuals in a county is associated with increases total deaths at end of study of 2067 (95% CI [1189, 2654]). Using data until the end of study, the same metric suggests ethnicity has double the association as the next most important factors, which are location, disease prevalence, and transit factors. Our findings shed light on societal patterns that have been reported and experienced in the U.S. by using robust methods to understand the features most responsible for transmission and sectors of society most vulnerable to infection and mortality. In particular, our results provide evidence of the disproportionate impact of the COVID-19 pandemic on minority populations. Our results suggest that mitigation measures, including how vaccines are distributed, could have the greatest impact if they are given with priority to the highest risk communities.more » « less
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Perennial grasslands, including prairie and pasture, have declined with tremendous environmental and social costs. This decline reflects unequal policy support for grasslands and managed grazing compared to row crops. To create a resource for community partners and decision-makers, we reviewed and analyzed the policy tools and implementation capacity that supports and constrains grasslands and managed grazing in the U.S. Upper Midwest. Risk reduction subsidies for corn and soybeans far outpace the support for pasture. Some states lost their statewide grazing specialist when the federal Grazing Lands Conservation Initiative lapsed. The United States Department of Agriculture, Natural Resources Conservation Service support for lands with prescribed grazing practices declined after 2005 but remained relatively steady 2010–2020. These results reveal the policy disadvantage for grasslands and managed grazing in comparison with row crop agriculture for milk and meat production. Grassland and grazing policies have an important nexus with water quality, biodiversity, carbon and outdoor recreation policy. Socially just transitions to well-managed, grazed grasslands require equity-oriented interventions that support community needs. We synthesized recommendations for national and state policy that farmers and other grazing professionals assert would support perennial grasslands and grazing, including changes in insurance, conservation programs, supply chains, land access, and fair labor. These policies would provide critical support for grass-based agriculture and prairies that we hope will help build soil, retain nutrients, reduce flooding and enhance biodiversity while providing healthy food, jobs, and communities.more » « less
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Background Stay-at-home orders were one of the controversial interventions to curb the spread of COVID-19 in the United States. The stay-at-home orders, implemented in 51 states and territories between March 7 and June 30, 2020, impacted the lives of individuals and communities and accelerated the heavy usage of web-based social networking sites. Twitter sentiment analysis can provide valuable insight into public health emergency response measures and allow for better formulation and timing of future public health measures to be released in response to future public health emergencies.
Objective This study evaluated how stay-at-home orders affect Twitter sentiment in the United States. Furthermore, this study aimed to understand the feedback on stay-at-home orders from groups with different circumstances and backgrounds. In addition, we particularly focused on vulnerable groups, including older people groups with underlying medical conditions, small and medium enterprises, and low-income groups.
Methods We constructed a multiperiod difference-in-differences regression model based on the Twitter sentiment geographical index quantified from 7.4 billion geo-tagged tweets data to analyze the dynamics of sentiment feedback on stay-at-home orders across the United States. In addition, we used moderated effects analysis to assess differential feedback from vulnerable groups.
Results We combed through the implementation of stay-at-home orders, Twitter sentiment geographical index, and the number of confirmed cases and deaths in 51 US states and territories. We identified trend changes in public sentiment before and after the stay-at-home orders. Regression results showed that stay-at-home orders generated a positive response, contributing to a recovery in Twitter sentiment. However, vulnerable groups faced greater shocks and hardships during the COVID-19 pandemic. In addition, economic and demographic characteristics had a significant moderating effect.
Conclusions This study showed a clear positive shift in public opinion about COVID-19, with this positive impact occurring primarily after stay-at-home orders. However, this positive sentiment is time-limited, with 14 days later allowing people to be more influenced by the status quo and trends, so feedback on the stay-at-home orders is no longer positively significant. In particular, negative sentiment is more likely to be generated in states with a large proportion of vulnerable groups, and the policy plays a limited role. The pandemic hit older people, those with underlying diseases, and small and medium enterprises directly but hurt states with cross-cutting economic situations and more complex demographics over time. Based on large-scale Twitter data, this sociological perspective allows us to monitor the evolution of public opinion more directly, assess the impact of social events on public opinion, and understand the heterogeneity in the face of pandemic shocks.
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/1745-9125.12275
