In June 2012, the Supreme Court of the United States ruled in Miller v. Alabama that mandatory life without-parole (LWOP) sentences were unconstitutional for individuals who were under the age of 18 at the time of their offense (hereafter, juveniles). In January 2016, the Supreme Court ruled in Montgomery v. Louisiana that Miller applied retroactively. Following Montgomery, individuals previously sentenced to mandatory LWOP as juveniles (hereafter, juvenile lifers) became eligible for resentencing. Accordingly, in almost all such cases, the district attorney’s office makes an offer for a new sentence to the defendant, who is free to accept the offer or to have his new sentence decided by the judge. In Philadelphia, re-sentence offers are decided by The Juvenile Lifer Resentencing Committee, which comprises 8 members of the executive staff at the District Attorney's Office. The author conducted semi-structured interviews with four members of the committee to understand the resentencing process and then performed a content analysis of the case-summary memos prepared by the lead assistant district attorney for each case to identify the case facts that were available for consideration by the committee. The authors present several key findings. One findings is that juvenile lifers can be considered low-impact releases in terms of risk posed to public safety. At the time of the analyses, 269 lifers have been re-sentenced in Philadelphia and 174 have been released. Six (3.5%) have been re-arrested. Charges were dropped in four of the cases and two (1%) resulted in new convictions (one for contempt and the other for robbery in the third degree). In comparison, nationally, an estimated 30% of individuals convicted of homicide offenses are rearrested within two years of release. Another finding is that overall, release of Philadelphia's juvenile lifers, to date, will result in an estimated minimum $9.5 million savings in correctional costs for Pennsylvania over the first decade.

This web resource provides information and visual dashboards related to six key policy decisions by state courts during the COVID-19 pandemic. The policy areas include jury trial restrictions, court operations, in-person court proceedings, remote oral arguments for state supreme courts, virtual hearings, and links to state court websites with information related to COVID-19. This resource notes that, in Florida, jury trial restrictions are in place through July 2020, the state has a statewide plan for resuming court operations, court in-person proceedings are suspended through July 2, 2020, and video conference arguments are permitted for the Florida Supreme Court.

This resource guides counties through the process of defining the most important cross-system changes to help reduce the number of people in jails who have serious mental illnesses. To reduce the prevalence of serious mental illness in jails, changes should address one or more of these four key measures: (1) the number of people booked into jail who have serious mental illnesses; (2) their average length of stay in jail; (3) how many people are connected to treatment and services; and (4) their recidivism rates. The recommendations include starting with baseline data, determining the projected effect of proposed improvements, prioritize potential high-impact strategies, work to obtain buy-in, and determine funding sources.

The National Center for Education Statistics surveyed 12,330 U.S. adults ages 16 to 74 living in households from 2012 to 2017 for the Program for the International Assessment of Adult Competencies (PIAAC), an international study involving over 35 countries. Using small area estimation models, the researchers produced indirect estimates of literacy and numeracy proficiency for all U.S. states and counties. According to this research, an estimated 24% of adults in Florida perform at the lowest literacy level and 35% perform at the lowest numeracy level. This puts Florida slightly below the national average on both metrics. Adults at the upper end of Level 1 can typically read short texts and understand the meaning well enough to perform simple tasks, such as filling out a basic form. Adults who are below Level 1 may be able to understand only very basic vocabulary or even struggle to do this. Approximately 34% of Florida adults are estimated to perform at Level 2 in literacy, and 42% function at Level 3 or above. Adults whose skills are below Level 3 are generally not considered to be fully proficient in working with information and ideas in text.

With increased tensions and political rhetoric surrounding immigration enforcement in the United States, schools are facing greater challenges in ensuring support for their students of immigrant and Latino/a origin. This study examined the associations between deportations near school districts and racial/ethnic gaps in educational outcomes in school districts across the country. With data from the Stanford Educational Data Archive, the Civil Rights Data Collection, and the Transactional Records Access Clearinghouse, this study used longitudinal, cross-sectional analyses and found that in the years when districts had more deportations occurring within 25 miles, White-Latino/a gaps were larger in math achievement and rates of chronic absenteeism. No associations were found for gaps in English language arts achievement or rates of bullying. Implications for researchers, policymakers, and school leaders are discussed.

The American Academy of Pediatrics recommends that U.S. secondary schools begin after 8:30 a.m. to better align with the circadian rhythms of adolescents. Yet due to economic and logistic considerations, the vast majority of high schools begin the school day considerably earlier. The leverage a quasi-natural experiment in which five comprehensive high schools in one of the nation’s largest school systems moved start times forty minutes earlier to better coordinate with earlier-start high schools. Here, disruption effects should exacerbate any harmful consequences. They report on the effect of earlier start times on a broad range of outcomes, including mandatory ACT test scores, absenteeism, on-time progress in high school, and college-going. While the authors fail to find evidence of harmful effects on test scores, they do see a rise in absenteeism and tardiness rates, as well as higher rates of dropping out of high school. These results suggest that the harmful effects of early start times may not be well captured by considering test scores alone.

Many state and local officials are making social-distancing policy decisions based on the actions of other locations rather than through a decision-making framework that evaluates these measures and their reduction of the spread of coronavirus disease 2019. To help provide one piece of that information, researchers developed a series of economic models aimed at filling in the gap and at estimating a rough order of magnitude of the economic consequences associated with a small set of social-distancing policies. The model examines five policy scenarios: 1) Close schools; 2) Close schools, bars, restaurants, and ban large events, 3) All of scenario 2 and close non-essential businesses, 4) All of scenario 3 and quarantine the most vulnerable, and 5) All of scenario 4 and quarantine all but essential workers. The models also examines a low-impact, baseline, and high-impact cases for each scenario. For Florida, the weekly percentage losses in income for these scenarios vary between 4.5% and 20.8%.

There are few silver linings to the COVID-19 pandemic, but free-flowing traffic is certainly one of them. For the essential workers who still must commute each day, driving to work has suddenly become much easier. The same applies to the trucks delivering surging e-commerce orders. Removing so many cars from the roads has even led to cleaner air, clearer views, and more room for outdoor recreation, even in major cities. Every metro area in the country experienced a traffic decline of at least 53% since the beginning of March. Still, the largest and smallest vehicle miles traveled drops tend to cluster in similar places. College towns such as Ann Arbor, Michigan, large metro areas along the Northeast corridor, and most of coastal California’s metro areas all saw their traffic levels drop by at least 75% since March 1. Meanwhile, many medium-sized metro areas in the South, running from Texas through the Carolinas, saw the smallest declines. Research finds that employers who offer more flexible work schedules tend to see more remote work occur. Regional business groups and large national companies should promote more flexible work, especially in some of the country’s most congested metro areas. Even small decreases in traffic can lead to huge time savings on the road. Now is the perfect time to account for driving’s high costs, and price it more appropriately. Private vehicles help us make trips at incredible speeds, but they have major consequences on the communities around us. Roadway fatalities are the first or second leading cause of unintentional death across all ages. Transportation is also the country’s top source of greenhouse gas emissions, with private vehicles the primary culprit. With gas prices at multi-decade lows, now is the ideal time to better reflect on driving’s social costs.

Economic and demographic data drive research, policy development, distribution of government resources, and private investment decisions. But many of the datasets that policymakers, practitioners, and researchers rely on to understand and guide resources to rural communities fall short in representing rural realities. Given the increasing attention to rural areas in public policy and popular discourse, along with notable trends disadvantaging rural places—persistent poverty and global economic shifts—this search for good rural data is timely. The report recommends the following additional measures be considered to identify policies and practices unique to rural areas: work readiness, individual health, owned assets, and seasonal employment. The report also recommends 1) increasing the size of rural samples in survey research; 2) trying new strategies to increase rural participation in important surveys like the American Community Survey; 3) reexamining practices around data suppression and noise as they relate to rural communities; and 4) for owners of proprietary data, partnering with government and university researchers to increase access to rural-specific data for the purpose of policy making and research.

Paid medical leave is a benefit that allows individuals to take time off from their jobs while continuing to receive their wages and salaries to address their own serious medical condition that limits their ability to work. The term medical leave generally refers to leave that lasts weeks or months. Research suggests that paid medical leave could affect economic outcomes by reducing income volatility, helping workers to return to employment after taking leave, reducing productivity loses due to presenteeism, and supporting greater labor supply and long-term labor force participation. There are several different mechanisms through which paid medical leave may have an effect on health outcomes. These include improved health management, earlier treatment, greater healthcare utilization, improved income stability, and reduced financial stress. The authors argue that future research should investigate several gaps in understanding including how worker use paid and unpaid leave, how outcomes may vary by sociodemographic characteristics, and how to most effectively provide return-to-work services.

Until a vaccine or effective antiviral treatment is available, managing the response to COVID-19 means moving beyond social distancing and testing in small numbers to include a variety of evidence-informed solutions that can help minimize the virus’s resurgence, reduce mortality rates, relieve overloaded health systems, safely re-open schools and businesses, facilitate economic recovery, and restore vibrant community connections. As an overarching response to these needs, there is a Curated Data, Modeling, and Policy Resources page to help policymakers COVID-19 locate the most valuable and trusted data and policy resources in the massive amount of available information. In addition, the COVID-19 Data Primer helps researchers, data scientists, and others looking to uncover insights from health care data better understand, track, and contain COVID-19. These materials are free to access and continually updated.

Thirty million workers filed initial unemployment claims between March 15 and April 25. As workers lose their jobs, many will also lose their employer-sponsored health insurance, as will their dependents. Some of these workers and dependents will qualify for Medicaid coverage, particularly in states that expanded Medicaid eligibility under the Affordable Care Act (ACA). Others will purchase individual coverage on the health insurance Marketplaces, possibly with a subsidy to offset the premium cost. And many will be unable to replace their employer-sponsored health insurance coverage and become uninsured. In this brief, the authors estimate how health insurance coverage could change as millions of workers lose their jobs during the COVID-19 recession. The authors present national and state-level estimates of coverage changes if unemployment rates rise from pre-crisis levels (around 3.5% nationally) to 15%, 20%, or 25%. For each unemployment level, they provide a base case scenario of coverage changes and a high scenario, derived from two different estimation methods. In the base scenario, the authors estimate that at 20% unemployment, approximately 25 million people will lose ESI coverage, and of them, 12 million would gain Medicaid coverage, 6 million would gain Marketplace or other private coverage, and 7 million would become uninsured. In the high scenario, the authors estimate that 43 million people would lose employer-sponsored health insurance coverage. The increase in Medicaid coverage and uninsurance rates will be uneven across the country, with a greater share of those estimated to lose employer-sponsored health insurance gaining Medicaid coverage and a lower share becoming uninsured in states that expanded Medicaid under the ACA.