Sociologists have long argued that the cultural construction of organizations as social actors underpins public expectations of corporate accountability. In recent decades, however, the unified bureaucratic structures that once sustained this construction have given way to increasingly fragmented and opaque organizational forms. This study considers to what extent the diffuse, often illegible nature of twenty-first century corporations undermines the ability of public audiences to demand corporate accountability. We argue that complex, fragmented organizational configurations allow firms to partially evade the negative reputational consequences of misconduct by confounding audiences and obfuscating the “actor” behind the bad organizational action. Drawing on a vignette- based survey experiment, we test whether fragmentation reduces attributions of blame following corporate wrongdoing. Consistent with our hypotheses, we find that while respondents generally attribute high levels of blame for wrongdoing, greater fragmentation decreases the blame directed at core firms and heightens audiences’ uncertainty about responsibility. Moreover, in fragmented structures, blame is not simply redistributed to auxiliary entities but is diminished overall. These findings suggest that as corporate structures grow more complex and less legible, the underlying actors behind organizational action become harder to identify and construct, and thereby harder to hold to account.

This article asks whether the experience of a boom-and-bust cycle renders economic actors more or less likely to engage in risky financial activities in the future. The financialization of U.S. households has occurred in the context of two successive mass-participatory asset bubbles: first in the stock market during the 1990s and later in the housing market during the 2000s. Behavioral economic theories predict that prior experience of market crashes should dampen speculative tendencies and prompt actors to behave more conservatively. By contrast, the authors build on the sociological literature about the financialization of daily life to develop an alternative hypothesis: that participation in financial markets increases actors' tendencies to engage in risky investment by socializing them to attend to novel market opportunities. The authors test these alternatives using panel data from the Panel Study of Income Dynamics and the National Longitudinal Survey of Youth 1979. Results from both control function and matched regression models reveal that those who participated more directly in the late 1990s stock market were more prone to invest aggressively in the mid-2000s housing market. These positive effects obtain irrespective of whether households gained or lost wealth during the bubble. The results provide new evidence about how financial capitalism is reshaping economic behavior.

Image recognition systems offer the promise to learn from images at scale without requiring expert knowledge. However, past research suggests that machine learning systems often produce biased output. In this article, we evaluate potential gender biases of commercial image recognition platforms using photographs of U.S. members of Congress and a large number of Twitter images posted by these politicians. Our crowdsourced validation shows that commercial image recognition systems can produce labels that are correct and biased at the same time as they selectively report a subset of many possible true labels. We find that images of women received three times more annotations related to physical appearance. Moreover, women in images are recognized at substantially lower rates in comparison with men. We discuss how encoded biases such as these affect the visibility of women, reinforce harmful gender stereotypes, and limit the validity of the insights that can be gathered from such data.

In On the Genealogy of Morality, Nietzsche derides scholars na€ıve enough to search for the origins of our moral commitments in their function. Simply because a moral belief helps to sustain the social order does not mean that it emerged to serve this role: “the cause of the origin of a thing and its eventual utility. lie worlds apart” [77]. Instead, a true “historical science” of morality looks not to function but to practice. How is morality used? By whom, when, and why? Whatever its historical accuracy, Nietzsche’s polemic threw down the gauntlet to those of us seeking to understand how contemporary moral commitments arise. Virtues do not innocently disclose their origins. We must look instead to the social contingencies from which they originated, however unflattering the ancestry. Stefan Bargheer’s masterful book Moral Entanglements: Conserving Birds in Britain and Germany engages in its own moral debunking project. Wielding a pragmatist approach as he investigates the genealogy of his moral subject, Bargheer’s explanatory adversary is not functionalism but rather those who emphasize the causal power of moral motivations. Our moral commitments, Bargheer argues, do not arise from moral discourse, ideology, or abstract principles. Morality instead arises from action and, crucially, “the institutional settings that facilitate this action” [20]. This pragmatist insight powers a several hundred-page exposition that spans two centuries, two countries, and countless organizations to follow the unlikely development of what, at first blush, appears to be a straightforward moral commitment: bird conservation. Moral Entanglements opens with a contradictory observation. The predecessors to modern-day bird conservationists, Bargheer argues, were bird hunters: “The very same people who initially killed birds and contributed to their extinction were also the first to protect them” [9]. More surprising still, the transformation from bird destruction to bird conservation was not a product of moral enlightenment or rational reflection. Rather, this moral transformation was unpremeditated, something one-time bird hunters more or less stumbled into as the technology, institutions, and politics surrounding them reshaped

This article challenges the implicit assumption of many cross-national studies that gender-role attitudes fall along a single continuum between traditional and egalitarian. The authors argue that this approach obscures theoretically important distinctions in attitudes and renders analyses of change over time incomplete. Using latent class analysis, they investigate the multidimensional nature of gender-role attitudes in 17 postindustrial European countries. They identify three distinct varieties of egalitarianism that they designate as liberal egalitarianism, egalitarian familism, and flexible egalitarianism. They show that while traditional gender-role attitudes have precipitously and uniformly declined in accordance with the rising tide narrative toward greater egalitarianism, the relative prevalence of different egalitarianisms varies markedly across countries. Furthermore, they find that European nations are not converging toward one dominant egalitarian model but rather, remain differentiated by varieties of egalitarianism.

This study examines whether self-monitoring—a ubiquitous social psychological construct that captures the extent to which individuals regulate their self-presentation to match the expectation of others—varies across demographic and social contexts. Building on Erving Goffman’s classic insights on stigma management, the authors expect that the propensity for self-monitoring will be greater among sexual minorities, especially in areas where the stigma surrounding minority sexual orientations is strong. The authors’ survey of U.S. adults shows that sexual minorities report significantly higher levels of self-monitoring than heterosexuals and that this difference disappears in large cities. These findings speak to sociological research on self-presentation, with implications for the literatures on identity formation, stigma management, and labor markets.

Numerous scholars have noted the disproportionately high number of gay and lesbian workers in certain occupations, but systematic explanations for this type of occupational segregation remain elusive. Drawing on the literatures on concealable stigma and stigma management, we develop a theoretical frame-work predicting that gay men and lesbians will concentrate in occupations that provide a high degree of task independence or require a high level of social perceptiveness, or both. Using several distinct measures of sexual orientation, and controlling for potential confounds, such as education, urban location, and regional and demographic differences, we find support for these predictions across two nationally representative surveys in the United States for the period 2008-2010. Gay men are more likely to be in female-majority occupations than are heterosexual men, and lesbians are more represented in male-majority occupations than are heterosexual women, but even after accounting for this tendency, common to both gay men and lesbians is a propensity to concentrate in occupations that provide task independence or require social perceptiveness, or both. This study offers a theory of occupational segregation on the basis of minority sexual orientation and holds implications for the literatures on stigma, occupations, and labor markets.

Over the past decades, ‘causal mechanisms’ have become an important part of social scientific explanation. Causal mechanisms now appear in annual review pieces, edited volumes, and occasional symposia. The publication of the Oxford Handbook of Analytic Sociology – a manifesto of the analytic paradigm that places mechanisms at the helm of its enterprise – is further evidence of this new focus. But what, precisely, are causal mechanisms? And how do they aid in explanation in the social sciences? This article investigates five major approaches to causal mechanisms toward the goal of identifying major points of consensus and contention. It further suggests that there are two distinct approaches to causal mechanisms: ‘top-down’ approaches that seek to generalize empirical events under widely instantiated causal patterns, and ‘bottom-up’ approaches that seek to disaggregate ‘average causal effects’ by opening up the ‘black-boxes.’

Research SummaryThis article reviews the causal turn in the social sciences and accompanying efforts by criminologists to make policy claims more credible. Although there has been much progress in techniques for the estimation of causal effects, we find that the link between evidence and valid policy implications remains elusive. Drawing on criminological theory and research insights from disciplines such as sociology, economics, and statistics, we assess principles and strategies for informing policy in a causally uncertain world. We identify three distinct domains of inquiry that form a part of the translational process from evidence to policy and that complicate the straightforward exportation of causal effects to policy recommendations: (a) mechanisms and causal pathways, (b) effect heterogeneity, and (c) contextualization. We elaborate these three concepts by examining research on broken windows theory, policing, video games and violence, the Moving to Opportunity voucher experiment, incarceration, and especially the rich set of experimental studies on domestic violence that originated in Minneapolis, MN in the early 1980s. We also articulate a set of conceptual tools for advancing the goal of policy translation and offer recommendations for how what we call “policy graphs”—causal graphs used to analyze the policy implications of a system of causal relations—can potentially integrate the theoretical and policy arms of criminology.Policy ImplicationsEvidence, even if causal, does not necessarily inform policy. In fact, the question of “what works,” the focus of the growing evidence‐based movement in criminology, turns out to be a different question than, “what will work?” Evidence‐based policy research must therefore be concerned with much more than providing policy makers with research on causal effects, however precisely measured. The implication is that we must separate criminology's increasing focus on causality from its policy turn and formally recognize that the latter requires a different standard of theory and evidence than does the former. In particular, criminologists interested in making policy claims must ask hard questions about the potential mechanisms through which a treatment influences an outcome, heterogeneous effects across people and time, contextual variations, and all of the real‐world phenomena to which these challenges give rise—such as unintended consequences, policies that change incentive and opportunity structures, and the scale at which policies change in meaning. Theoretically guided causal graphs enhance this goal and help inform policy in a causally uncertain world. Translational criminology is ultimately a process that entails the constant interplay of theory, research, and practice.

Research SummaryThis article reviews the causal turn in the social sciences and accompanying efforts by criminologists to make policy claims more credible. Although there has been much progress in techniques for the estimation of causal effects, we find that the link between evidence and valid policy implications remains elusive. Drawing on criminological theory and research insights from disciplines such as sociology, economics, and statistics, we assess principles and strategies for informing policy in a causally uncertain world. We identify three distinct domains of inquiry that form a part of the translational process from evidence to policy and that complicate the straightforward exportation of causal effects to policy recommendations: (a) mechanisms and causal pathways, (b) effect heterogeneity, and (c) contextualization. We elaborate these three concepts by examining research on broken windows theory, policing, video games and violence, the Moving to Opportunity voucher experiment, incarceration, and especially the rich set of experimental studies on domestic violence that originated in Minneapolis, MN in the early 1980s. We also articulate a set of conceptual tools for advancing the goal of policy translation and offer recommendations for how what we call "policy graphs"- causal graphs used to analyze the policy implications of a system of causal relations- can potentially integrate the theoretical and policy arms of criminology.Policy ImplicationsEvidence, even if causal, does not necessarily inform policy. In fact, the question of "what works," the focus of the growing evidence-based movement in criminology, turns out to be a different question than, "what will work?" Evidence-based policy research must therefore be concerned with much more than providing policy makers with research on causal effects, however precisely measured. The implication is that we must separate criminology's increasing focus on causality from its policy turn and formally recognize that the latter requires a different standard of theory and evidence than does the former. In particular, criminologists interested in making policy claims must ask hard questions about the potential mechanisms through which a treatment influences an outcome, heterogeneous effects across people and time, contextual variations, and all of the real-world phenomena to which these challenges give rise-such as unintended consequences, policies that change incentive and opportunity structures, and the scale at which policies change in meaning. Theoretically guided causal graphs enhance this goal and help inform policy in a causally uncertain world. Translational criminology is ultimately a process that entails the constant interplay of theory, research, and practice.

Much of social science is concerned with providing a warrant, that is, convincing evidence, for causal claims of interest. Generally, one is interested in the effect of a cause, sometimes referred to as the treatment, on an outcome. There are two basic evidentiary strategies for supporting causal claims. One approach is to carry out an experiment where the researcher controls the treatment and all other factors are held constant. A closely related alternative is to mimic the experiment, by attempting to hold other explanatory variables constant through stratification, matching, or regression. This general approach has dominated the social sciences for decades. A second, quite distinct strategy is to posit and find evidence for, the mechanisms that link cause and effect. Often this is done by specifying one or more mediating variables and by demonstrating that: first, they have been affected by the treatment and second, they have affected the outcome. Over the past decade, researchers have paid increased attention to causal mechanisms as an important aspect of sociological inquiry. While the term some have used to describe to this resurgence--a “mechanistic revolution”–may be a bit of an exaggeration, it is clear that increasingly researchers regard the elaboration of causal relations as necessary for adequate explanation. As

Public lighting improves visibility and provides orientation. It also contributes to the perception of comfort and safety of people outside after dark. At present, highpressure sodium lamps are widely used in street lighting. This is in part due to their high efficacy and relatively long lifetime (≥16 000 hours). Their use, however, comes at the expense of good colour rendering. Recently developed ceramic metal halide lamps provide many of the advantages of HPS in addition to white light and better rendering of colours. In this paper, results of research conducted in three European countries on the effect of lamp spectrum on face recognition and the perception of safety and comfort outdoors are presented. The results consistently show that at comparable illuminances, people perceive areas illuminated with white light to be brighter, safer and more comfortable than the same neighbourhood illuminated with yellowish light.

Extant research on the cost of the death penalty consistently finds that pursuit of a death sentence adds costs to case processing. However, these studies have important limitations in either the sampling frame or in their failure to include adequate statistical controls. This research draws upon a rich dataset of capital-eligible cases in Maryland to estimate the additional cost of filing a death notice. Multivariate models are used to control for selection into capital case processing and for competing explanations of cost. We find that filing a death notice is associated with an additional one million dollars in costs.