This report presents statistics from the U.S. Bureau of Justice Statistic’s National Crime Victimization Survey (NCVS) and the Federal Bureau of Investigation’s (FBI) Uniform Crime Reporting Program Summary Reporting System (UCR SRS), both of which measure the magnitude, nature, and impact of crime in the nation. The NCVS was established in 1973 to complement the UCR SRS and measure crimes not reported to police. The NCVS and UCR SRS have different purposes, use different methods, and focus on different aspects of crime. The information they produce together provides a comprehensive understanding of crime in the United States. This report presents NCVS and UCR SRS statistical estimates as defined by each program. The report finds that during the 10-year period from 2011 to 2020, the NCVS rate of violent crime declined from 22.6 to 16.4 victimizations per 1,000 persons age 12 or older. During the same 10-year period, the UCR SRS rate of violent crime remained steady around 4.0 crimes per 1,000 persons. Additionally, from 2019 to 2020, the NCVS rate of violent crime reported to police decreased from 8.6 to 6.6 per 1,000 persons age 12 or older (down 23%), while the UCR SRS violent crime rate increased marginally from 3.8 per 1,000 persons in 2019 to 4.0 per 1,000 in 2020.

The authors investigate what portion of the pool of unemployed men in the United States have been arrested, convicted, or incarcerated by age 35. Using the National Longitudinal Survey of Youth, 1997, they estimate 64% of unemployed men have been arrested, and 46% have been convicted. Unexpectedly, these rates vary only slightly by race and ethnicity. Further investigation of other outcomes such as marriage, education, household net worth, and earnings shows large differences between unemployed men who have a criminal history record and those who do not. One major implication of these findings is that employment services should focus more on the special challenges facing unemployed men with criminal history records. A second implication is that statistical discrimination against unemployed members of racial minority groups, to avoid hiring those with criminal histories, is both illegal and ineffective.

gun violence is tightly concentrated on a small number of very high risk young Black male adults that share a common set of risk factors, including: involvement in street crews/groups; significant criminal justice history including prior or active community supervision; often prior victimization; and a connection to a recent shooting (within the past 12 months). Often shootings are precipitated by a petty conflict over a young woman, a simple argument, or the now ubiquitous social media slight. Exacerbating the social media incited shootings are music videos that promote certain neighborhoods or cliques that also “dis” other crews or individuals, sparking a series of comments and competing videos that escalate into shootings. All of this is made possible and exacerbated by the wide availability of firearms and the culture of resolving conflicts through violence. This small number of very high risk individuals are identifiable, their violence is predictable, and therefore it is preventable. Based on the assessment of data and the series of interviews conducted, the authors estimate that within a year, there are at least 500 identifiable people who rise to this level of very high risk, and likely no more than 200 at any one given time. These individuals comprise approximately 60-70% of all gun violence in the District. The authors recommend that the District establish a clear citywide strategy that focuses intentional, structured, and intensive intervention efforts on those individuals identified as being at very high risk of being involved in gun violence.

The metaverse is here. Though there are various definitions of metaverse, each speaks of a space that is a combination of virtual and live—creating a third space that is not that is not home or work. Soon it will be as omnipresent as TikTok, Instagram, and Facebook (now Meta). As technology advances to bring us new immersive and imaginary worlds, the education of children and the preparation of teachers must also advance to meet these new opportunities. When education lags the digital leaps, the technology rather than educators defines what counts as educational opportunity. This is largely what happened with the introduction of applications (apps) designed to be used on smartphones and tablets meant for adults. Today, as the metaverse infrastructure is still under construction, researchers, educators, policymakers, and digital designers have a chance to lead the way rather than get caught in the undertow. To leverage the potential of the metaverse as a 3D, global, interconnected, immersive, and real-time online space, we need new ways to connect the physical world with augmented and virtual reality experiences. The metaverse of the future is likely to fully support augmented and virtual reality, artificial intelligence, and the connectivity to link all worlds. Indeed, in its most democratic instantiation, anyone will have the opportunity to create a space and be part of a user-generated global community on an interoperable multiplatform where they can share their games or goods with the world. The 5G internet speed should allow this to be a reality. This report offers a path for bringing best educational practices into the metaverse. The authors suggest a series of well-worn principles derived from the science of how and what children learn to guide the design of new educational technology. They also suggest ways in which design in this new space can go astray. In the end, the authors challenge those creating educational products for the metaverse to partner with educators and scientists to ensure that children experience real human social interaction as they navigate virtual spaces, children’s agency is supported as they explore these spaces, and there is a real eye to diversity in the representation and access to what is created.

In response to disruptions to work, school, and home life that all Americans have experienced during the COVID-19 pandemic, most federal student loans have been paused until May 1, 2022, affecting roughly 24 million people. Evidence of the effects of the pandemic on student loan borrowers is still emerging. In this report, the authors provide a descriptive look at the financial behavior of student loan borrowers during the pandemic pause, relative to nonborrowers. Specifically, they look at the likelihood of obtaining a first mortgage or auto loan during this time. The results suggest the need for a careful evaluation of the effect of the pandemic student loan pause, and other policies, on student loan borrowers’ finances, homebuying, and wealth. The authors find a substantial increase in first-time homebuying among student loan borrowers during the pause, relative to nonborrowers. This increase persists even after controlling for age, credit score, and zip code characteristics. However, this effect is largely driven by student loan borrowers who were in repayment just before the pandemic. Borrowers who were in default before the pandemic were substantially less likely than nonborrowers to obtain a first mortgage during the pause, even after including available controls. Policies during the pandemic such as federal stimulus payments and expanded social safety net benefits—in addition to the student loan pause–may have stabilized, or improved, some borrowers’ financial standing. But all have faced the risk of COVID-19 infection, the effects of isolation from others, and disruption to employment and workplace environments. These results suggest that borrowers who were struggling with repayment before the pandemic may still need support after the pause ends.

Following each national election, the U.S. Census Bureau conducts the Current Population Survey’s November Voting and Registration Supplement. The supplement is fielded following both presidential elections when congressional seats and the presidency are decided, and midterm elections when congressional seats are the highest offices decided. The Current Population Survey has surveyed Americans eligible to vote in these elections since 1964, and estimates derived from this survey are among the most consistently reliable and publicly available estimates of the characteristics of American voters. Held during a global pandemic, the 2020 presidential election featured record turnout and record use of non-traditional voting. The November 2020 the Current Population Survey Voting and Registration Supplement provides a detailed look at the demographics of who voted, the methods voters used to vote, and how these measures have changed over time. The largest age group of voters was the one between ages 45–64, constituting just over one-third of all voters in 2020 (34.7%). This group shrank from 37.6% of voters in 2016 to its lowest share since 1996. The oldest age group, those 65 or older, made up 25.7% of 2020 voters. This is the largest voter share for those 65 and older on record in the survey’s time series. The youngest age groups, those 18–29 years old and those 30–44 years old, grew to 16.5% and 23.2%, respectively.

The Financial Report of the U.S. Government provides a comprehensive view of government finances, including revenues, costs, assets, liabilities, long-term sustainability, and the financial impact of the federal COVID-19 response. The Government Accountability Office (GAO) audits the financial statements in that report each year, but they have not yet been able to determine if they fairly present the government's finances. This year, it continued to be primarily due to serious financial management problems at the U.S. Defense Department and Small Business Administration; unresolved differences in balances between federal agencies; and weaknesses in the process for preparing the statements. The comprehensive long-term fiscal projections presented in the Statement of Long-Term Fiscal Projections and related information show that based on current revenue and spending policies, the federal government continues to face an unsustainable long-term fiscal path. Since 2017, GAO has stated that a fiscal plan is needed to ensure that the U.S. remains in a strong economic position to meet its social and security needs, as well as to preserve flexibility to address unforeseen events like public health emergencies. Congress and the administration have responded in an unprecedented manner to the COVID-19 pandemic and the resulting severe economic repercussions. Once the pandemic recedes and as the economy continues to recover, Congress and the administration should quickly pivot to developing a plan to place the federal government on a sustainable long-term fiscal path. Further, GAO has recommended that Congress consider alternative approaches to the current debt limit as part of any long-term fiscal plan.

Social equity has become a key concern among public agencies. In 2020, the California Public Utilities Commission adopted D. 20-08-046, Decision on Energy Utility Climate Change Vulnerability Assessments and Climate Adaptation in Disadvantaged Communities. This ruling requires utilities to engage disadvantaged communities and assess their vulnerability to climate impacts. It also requires utilities to evaluate how their climate adaptation efforts can promote equity. Equity is a sense of fairness and speaks to differences in experiences and outcomes among disparate groups. Energy equity is the sense of fairness applied to the power sector. In the context of this work on distributional equity, equity metrics measure how costs and benefits of a system or intervention accrue to different groups. Southern California Edison, the sponsor of this work, is one of several investor-owned utilities regulated by the California Public Utilities Commission that must adhere to this rulemaking. The authors developed an illustrative set of context-specific equity metrics that Southern California Edison could build on and incorporate into its ongoing work toward climate adaptation. These metrics can help inform utility regulators and electricity utilities as they begin grappling with energy equity. It offers a straightforward methodology and a starting set of equity metrics that are intended to be adapted to different contexts. The following equity metrics are a useful starting point for assessing equity in its projects: investment, employment, participation, electricity burden, implementation cost share, System Average Interruption Duration Index, System Average Interruption Frequency Index, account attrition because of non-payment, hospitalization rates, weighted value of lost load for businesses and households, and community benefit.

Racial wealth inequality has been pervasive in the United States from the earliest days of colonization 400 years ago. Despite constitutional guarantees of equality and numerous anti-discrimination laws, racial wealth gaps not only remain but some are growing. Scholars, policymakers, and others have deeply investigated the historical roots and current drivers of racial wealth inequality in the United States. Most analyses focus on total asset holdings, intergenerational transfers, or disparities in specific assets (such as home equity). Media coverage and social narratives about racial wealth gaps similarly tend to concentrate on assets. Less attention has been paid to the other side of the household balance sheet: debt. Although there has been analysis of racial disparities in mortgages, and recent research has illuminated the role of student loans in widening the wealth gap between Black and White households, debt remains underappreciated as a driver of racial wealth gaps. This report explores the links between racial disparities in debt and those in wealth. It reflects findings from a literature review, interviews with experts from the academic and private sectors, analysis of federal survey data, and focus groups and consumer surveys. The authors believe that fully understanding the impact of debt on people’s lives requires a multidisciplinary approach that includes systematically seeking input from and listening to people who struggle financially. This report provides a resource for leaders across sectors to understand more deeply the interactions between racial disparities in debt and racial gaps in wealth and the ways in which redressing the racial wealth gap requires addressing racial debt disparities.

This report presents national estimates of different types of health insurance coverage and lack of coverage (uninsured). Estimates are presented by selected sociodemographic characteristics, including age, sex, race and Hispanic origin, family income, education level, employment status, and marital status. In 2020, 31.6 million (9.7%) people of all ages were uninsured at the time of the interview. This includes 31.2 million (11.5%) people under age 65. Among children, 3.7 million (5.0%) were uninsured, and among working-age adults (aged 18–64), 27.5 million (13.9%) were uninsured. Among people under age 65, 64.3% were covered by private health insurance, including 56.6% with employment-based coverage and 6.7% with directly purchased coverage. Moreover, 4.0% were covered by exchange-based coverage, a type of directly purchased coverage. Among people under age 65, about two in five children and one in five adults were covered by public health coverage, mainly by Medicaid and the Children’s Health Insurance Program. Among adults aged 65 and over, the percentage who were covered by private health insurance (with or without Medicare), Medicare Advantage, and traditional Medicare only varied by age, family income level, education level, and race and Hispanic origin.

Gender-based disparities in compensation in academic medicine are recognized, but their estimated impacts on early career earning potential and strategies to mitigate them have not been well studied. The purpose of this study is to compare earning potential between female and male academic physicians in the first 10 years of post-training employment and to evaluate the estimated impact of promotion timing, starting salary, and salary growth rate on earning potential. Using publicly available mean debt and compensation data for full-time employed academic physicians in the U.S. from 2019 to 2020, starting salary, salary in year 10 of employment, annual salary growth rate, and overall earning potential in the first 10 years of employment were estimated for each gender by subspecialty. This cross-sectional study included compensation data from 24,593 female and 29,886 male academic physicians across 45 subspecialties. Women had lower starting salaries in 42 of 45 subspecialties (93%), year-10 salaries in 43 of 45 subspecialties (96%), mean annual salary growth rates in 22 of 45 subspecialties (49%), and earning potential in 43 of 45 subspecialties (96%). A 1-year delay in promotion from assistant to associate professor reduced women’s earning potential by a median of $26,042 ($19,672-$35,671), but failure to be promoted at all reduced it by a median of $218,724 ($176,317-$284,466). Equalizing starting salaries could increase women’s earning potential by a median of $250 075 ($161,299-$381,799) in the subspecialties for which starting salaries for women were lower than those for men. Equalizing annual salary growth rates could increase women’s earning potential by a median (IQR) of $53,661 ($24,258-$102,892) in the subspecialties for which mean annual salary growth rates were lower for women than for men. The findings of this study suggest that gender-based disparities in starting salary and early career earning potential are pervasive in academic medicine in the U.S. Equalizing starting salaries would address the majority of the differences in earning potential.

While a growing body of evidence documents large gender disparities in health care and related social insurance programs, little is known about what drives these disparities. The authors leverage administrative data and random assignment of doctors to patients inherent within the workers’ compensation insurance claim dispute resolution process to study the impact of gender match between doctors and patients on medical evaluations and subsequent social insurance benefits received. Compared to differences among their male patient counterparts, female patients randomly assigned a female doctor rather than a male doctor are 5% more likely to be evaluated as disabled and receive 8.5% more subsequent cash benefits on average. There is no analogous gender-match effect for male patients. The magnitude of these effects implies that having female doctors evaluate patients entirely offsets the observed gender gap in the likelihood of being evaluated as disabled when male doctors evaluate patients. The authors explore mechanisms through further analysis of the administrative data and complementary survey evidence. In addition, the authors present broader evidence on gender gaps in workers' compensation insurance and gender homophily in patients' selections of doctors in settings where patients have choice. Combining this evidence, the authors conduct policy counterfactuals illustrating how policies increasing gender diversity among doctors or increasing gender homophily in patient-doctor matches may impact gender gaps in evaluated disability. The findings indicate that policies increasing the share of female patients evaluated by female doctors may substantially shrink gender gaps in medical evaluations and associated outcomes.