Knowledge about others reduces one's own sense of anonymity.

Social ties often seem symmetric, but they need not be1-5. For example, a person might know a stranger better than the stranger knows them. We explored whether people overlook these asymmetries and what consequences that might have for people's perceptions and actions. Here we show that when people know more about others, they think others know more about them. Across nine laboratory experiments, when participants learned more about a stranger, they felt as if the stranger also knew them better, and they acted as if the stranger was more attuned to their actions. As a result, participants were more honest around known strangers. We tested this further with a field experiment in New York City, in which we provided residents with mundane information about neighbourhood police officers. We found that the intervention shifted residents' perceptions of officers' knowledge of illegal activity, and it may even have reduced crime. It appears that our sense of anonymity depends not only on what people know about us but also on what we know about them.

Partners in Crime: Clandestine Operations among RAS-RAF Accomplices in Promoting Tumorigenesis.

In this issue of Molecular Cell, Terrell et al. (2019) characterize the interactions of RAS-RAF complexes in live cells. Using bioluminescence resonance energy transfer (BRET) technology, they show that individual RAF family members exhibit distinct binding affinities to each RAS family protein, with CRAF exhibiting high binding affinities for all RAS proteins and BRAF exhibiting increased binding affinity for KRAS.

Do digital technologies reduce racially biased reporting? Evidence from NYPD administrative data.

Recent work has emphasized the disproportionate bias faced by minorities when interacting with law enforcement. However, research on the topic has been hampered by biased sampling in administrative data, namely that records of police interactions with citizens only reflect information on the civilians that police elect to investigate, and not civilians that police observe but do not investigate. In this work, we address a related bias in administrative police data which has received less empirical attention, namely reporting biases around investigations that have taken place. Further, we investigate whether digital monitoring tools help mitigate this reporting bias. To do so, we examine changes in reports of interactions between law enforcement and citizens in the wake of the New York City Police Department's replacement of analog memo books with mobile smartphones. Results from a staggered difference in differences estimation indicate a significant increase in reports of citizen stops once the new smartphones are deployed. Importantly, we observe that the rise is driven by increased reports of "unproductive" stops, stops involving non-White citizens, and stops occurring in areas characterized by a greater concentration of crime and non-White residents. These results reinforce the recent observation that prior work has likely underestimated the extent of racial bias in policing. Further, they highlight that the implementation of digital monitoring tools can mitigate the issue to some extent.

Understanding the relationship between intergenerational mobility and community violence.

Violence is a key mechanism in the reproduction of community disadvantage. The existing evidence indicates that violence in a community impacts the intergenerational mobility of its residents. The current study explores the possibility of a reverse relationship. This study provisionally tests the hypothesis that depressed intergenerational mobility in a community may also spark subsequent community violence. We deploy a county measure of intergenerational mobility captured during early adulthood for a cohort of youth born between 1980 and 1986 and raised in low-income families [R. Chetty, N. Hendren, Quart. J. Econom. 133, 1163-1228 (2018)]. We model the relationship between county mobility scores and two county-level outcomes: violent crime and homicide. We find that a county's level of intergenerational mobility as measured by the Chetty-Hendren data is a major predictor of its rate of violent crime and homicide in 2008, when the youth in Chetty's mobility cohort were young adults (the same age the mobility measure was captured). In fact, mobility is a significantly stronger and more consistent predictor of community violent crime and homicide rates than more commonly used factors like poverty, inequality, unemployment, and law enforcement presence.

Organized crime in the fisheries sector threatens a sustainable ocean economy.

The threat of criminal activity in the fisheries sector has concerned the international community for a number of years. In more recent times, the presence of organized crime in fisheries has come to the fore. In 2008, the United Nations General Assembly asked all states to contribute to increasing our understanding the connection between illegal fishing and transnational organized crime at sea. Policy-makers, researchers and members of civil society are increasing their knowledge of the dynamics and destructiveness of the blue shadow economy and the role of organized crime within this economy. Anecdotal, scientific and example-based evidence of the various manifestations of organized crime in fisheries, its widespread adverse impacts on economies, societies and the environment globally and its potential security consequences is now publicly available. Here we present the current state of knowledge on organized crime in the fisheries sector. We show how the many facets of organized crime in this sector, including fraud, drug trafficking and forced labour, hinder progress towards the development of a sustainable ocean economy. With reference to worldwide promising practices, we highlight practical opportunities for action to address the problem. We emphasize the need for a shared understanding of the challenge and for the implementation of intelligence-led, skills-based cooperative law enforcement action at a global level and a community-based approach for targeting organized crime in the supply chain of organized criminal networks at a local level, facilitated by legislative frameworks and increased transparency.

The secret life of crime labs.

Houston TX experienced a widely known failure of its police forensic laboratory. This gave rise to the Houston Forensic Science Center (HFSC) as a separate entity to provide forensic services to the City of Houston. HFSC is a very large forensic laboratory and has made significant progress at remediating the past failures and improving public trust in forensic testing. HFSC has a large and robust blind testing program, which has provided many insights into the challenges forensic laboratories face. HFSC's journey from a notoriously failed lab to a model also gives perspective to the resource challenges faced by all labs in the country. Challenges for labs include the pervasive reality of poor-quality evidence. Also that forensic laboratories are necessarily part of a much wider system of interdependent functions in criminal justice making blind testing something in which all parts have a role. This interconnectedness also highlights the need for an array of oversight and regulatory frameworks to function properly. The major essential databases in forensics need to be a part of blind testing programs and work is needed to ensure that the results from these databases are indeed producing correct results and those results are being correctly used. Last, laboratory reports of "inconclusive" results are a significant challenge for laboratories and the system to better understand when these results are appropriate, necessary and most importantly correctly used by the rest of the system.

Commemorating local victims of past atrocities and far-right support over time.

Does public remembrance of past atrocities lead to decreased support for far-right parties today? Initiatives commemorating past atrocities aim to make visible the victims and crimes committed against them. This runs counter to revisionist actors who attempt to downplay or deny atrocities and victims. Memorials for victims might complicate such attempts and reduce support for revisionist actors. Yet, little empirical evidence exists on whether that happens. In this study, we examine whether exposure to local memorials that commemorate victims of atrocities reduces support for a revisionist far-right party. Our empirical case is the Stolpersteine ("stumbling stones") memorial in Berlin, Germany. It commemorates victims and survivors of Nazi persecution in front of their last freely chosen place of residence. We employ time-series cross-sectional analyses and a discontinuity design using a panel dataset that matches the location and date of placement of new Stolpersteine with the election results from seven elections (2013 to 2021) at the level of polling station areas. We find that, on average, the presence of Stolpersteine is associated with a 0.96%-point decrease in the far-right vote share in the following election. Our study suggests that local memorials that make past atrocities visible have implications for political behavior in the present.

Hate crime supporters are found across age, gender, and income groups and are susceptible to violent political appeals.

Hate crime is a pervasive problem across societies. Though perpetrators represent a small share of the population, their actions continue in part because they enjoy community support. But we know very little about this wider community of support; existing surveys do not measure whether citizens approve of hate crime. Focusing on Germany, where antiminority violence is entrenched, this paper uses original surveys to provide systematic evidence on the nature and impacts of hate crime support. Employing direct and indirect measures, I find that significant shares of the population support antirefugee hate crime and that the profile of supporters is broad, going much beyond common perpetrator types. I next use a candidate choice experiment to show that this support has disturbing political consequences: among radical right voters, hate crime supporters prefer candidates who endorse using gun violence against refugees. I conclude that a significant number of citizens empower potential perpetrators from the bottom-up and further legitimize hate crime from the top-down by championing violence-promoting political elites.

Cohort bias in predictive risk assessments of future criminal justice system involvement.

Risk assessment instruments (RAIs) are widely used to aid high-stakes decision-making in criminal justice settings and other areas such as health care and child welfare. These tools, whether using machine learning or simpler algorithms, typically assume a time-invariant relationship between predictors and outcome. Because societies are themselves changing and not just individuals, this assumption may be violated in many behavioral settings, generating what we call cohort bias. Analyzing criminal histories in a cohort-sequential longitudinal study of children, we demonstrate that regardless of model type or predictor sets, a tool trained to predict the likelihood of arrest between the ages of 17 and 24 y on older birth cohorts systematically overpredicts the likelihood of arrest for younger birth cohorts over the period 1995 to 2020. Cohort bias is found for both relative and absolute risks, and it persists for all racial groups and within groups at highest risk for arrest. The results imply that cohort bias is an underappreciated mechanism generating inequality in contacts with the criminal legal system that is distinct from racial bias. Cohort bias is a challenge not only for predictive instruments with respect to crime and justice, but also for RAIs more broadly.

How to make better forensic decisions.

Much of forensic practice today involves human decisions about the origins of patterned sensory evidence, such as tool marks and fingerprints discovered at a crime scene. These decisions are made by trained observers who compare the evidential pattern to an exemplar pattern produced by the suspected source of the evidence. The decision consists of a determination as to whether the two patterns are similar enough to have come from the same source. Although forensic pattern comparison disciplines have for decades played a valued role in criminal investigation and prosecution, the extremely high personal and societal costs of failure-the conviction of innocent people-has elicited calls for caution and for the development of better practices. These calls have been heard by the scientific community involved in the study of human information processing, which has begun to offer much-needed perspectives on sensory measurement, discrimination, and classification in a forensic context. Here I draw from a well-established theoretical and empirical approach in sensory science to illustrate the vulnerabilities of contemporary pattern comparison disciplines and to suggest specific strategies for improvement.

Police agencies on Facebook overreport on Black suspects.

A large and growing share of the American public turns to Facebook for news. On this platform, reports about crime increasingly come directly from law enforcement agencies, raising questions about content curation. We gathered all posts from almost 14,000 Facebook pages maintained by US law enforcement agencies, focusing on reporting about crime and race. We found that Facebook users are exposed to posts that overrepresent Black suspects by 25 percentage points relative to local arrest rates. This overexposure occurs across crime types and geographic regions and increases with the proportion of both Republican voters and non-Black residents. Widespread exposure to overreporting risks reinforcing racial stereotypes about crime and exacerbating punitive preferences among the polity more generally.

Unexpected employee location is associated with injury during robberies.

Millions of employees are victims of violent crimes at work every year, particularly those in the retail industry, who are frequent targets of robbery. Why are some employees injured while others escape from these incidents physically unharmed? Departing from prevailing models of workplace violence, which focus on the static characteristics of perpetrators, victims, and work environments, we examine why and when injuries during robberies occur. Our multimethod investigation of convenience-store robberies sought evidence from detailed coding of surveillance videos and matched archival data, preregistered experiments with formerly incarcerated individuals and customer service personnel, and a 3-y longitudinal intervention study in the field. While standard retail-industry safety protocols encourage employees to be out from behind the cash register area to be safer, we find that robbers are significantly more likely to injure or kill employees who are located there (versus behind the cash register area) when a robbery begins. A 3-y field study demonstrates that changing the safety training protocol-through providing employees with a behavioral script to follow should a robbery begin when they are on the sales floor-was associated with a significantly lower rate of injury during these robberies. Our research establishes the importance of understanding the interactive dynamics of workplace violence, crime, and conflict.

Implicit data crimes: Machine learning bias arising from misuse of public data.

SignificancePublic databases are an important resource for machine learning research, but their growing availability sometimes leads to "off-label" usage, where data published for one task are used for another. This work reveals that such off-label usage could lead to biased, overly optimistic results of machine-learning algorithms. The underlying cause is that public data are processed with hidden processing pipelines that alter the data features. Here we study three well-known algorithms developed for image reconstruction from magnetic resonance imaging measurements and show they could produce biased results with up to 48% artificial improvement when applied to public databases. We relate to the publication of such results as implicit "data crimes" to raise community awareness of this growing big data problem.

Reforming the police through procedural justice training: A multicity randomized trial at crime hot spots.

SignificanceOur study is a randomized trial in policing confirming that intensive training in procedural justice (PJ) can lead to more procedurally just behavior and less disrespectful treatment of people at high-crime places. The fact that the PJ intervention reduced arrests by police officers, positively influenced residents' perceptions of police harassment and violence, and also reduced crime provides important guidance for police reform in a period of strong criticism of policing. This randomized trial points to the potential for PJ training not simply to encourage fair and respectful policing but also to improve evaluations of the police and crime prevention effectiveness.

Activity-adjusted crime rates show that public safety worsened in 2020.

This paper argues that changes in human activity during the COVID-19 pandemic led to an unusual divergence between crime rates and victimization risk in US cities. Most violent crimes declined during the pandemic. However, analysis using data on activity shows that the risk of street crime victimization was elevated throughout 2020. People in public spaces were 15 to 30% more likely to be robbed or assaulted. This increase is unlikely to be explained by changes in crime reporting or selection into outdoor activities by potential victims. Traditional crime rates may present a misleading view of the recent changes in public safety.

14-Carbon demonstrates that some illegal ivory is being taken from government stockpiles.

The 14-carbon in animal tissues records the time that the tissues are formed; since the 1960s, using the "bomb curve" for 14C, the age of animal death can be determined accurately. Using animal tissue samples of known collection and formation dates for calibration, we determine the age of ivory samples from four ivory seizures made by law enforcement agencies between 2017 and 2019. The 14C measurements from these seizures show that most ivory in the illegal wildlife trade is from animals from recent poaching activities. However, one seizure has a large fraction of ivory that is more than 30 y old, consistent with markings on the tusks indicating they were derived from a government stockpile.

Multivariate Bayesian spatio-temporal P-spline models to analyze crimes against women.

Univariate spatio-temporal models for areal count data have received great attention in recent years for estimating risks. However, models for studying multivariate responses are less commonly used mainly due to the computational burden. In this article, multivariate spatio-temporal P-spline models are proposed to study different forms of violence against women. Modeling distinct crimes jointly improves the precision of estimates over univariate models and allows to compute correlations among them. The correlation between the spatial and the temporal patterns may suggest connections among the different crimes that will certainly benefit a thorough comprehension of this problem that affects millions of women around the world. The models are fitted using integrated nested Laplace approximations and are used to analyze four distinct crimes against women at district level in the Indian state of Maharashtra during the period 2001-2013.

Viruses in neurodegenerative diseases: More than just suspects in crimes.

Neurodegenerative diseases (NDs) such as Alzheimer's and Parkinson's disease are fatal neurological diseases that can be of idiopathic, genetic, or even infectious origin, as in the case of transmissible spongiform encephalopathies. The etiological factors that lead to neurodegeneration remain unknown but likely involve a combination of aging, genetic risk factors, and environmental stressors. Accumulating evidence hints at an association of viruses with neurodegenerative disorders and suggests that virus-induced neuroinflammation and perturbation of neuronal protein quality control can be involved in the early steps of disease development. In this review, we focus on emerging evidence for a correlation between NDs and viral infection and discuss how viral manipulations of cellular processes can affect the formation and dissemination of disease-associated protein aggregates.