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We study how electoral systems affect the presence of women in politics using a model in which both voters and parties might have a gender bias. We apply the model to Spanish municipal elections, in which national law mandates that municipalities follow one of two different electoral systems: a closed-list system in which voters pick one party-list, or an open-list system, in which voters pick individual candidates. Using a regression discontinuity design, we find that the closed-list system increases the share of women among candidates and councilors by 2.5 percentage points, and the share of women among mayors by 4.3 percentage points. Our model explains these results as mostly driven by voter bias against women. We provide evidence that supports the mechanism of the model. In particular, we show that, when two councilors almost tied in general-election votes, the one with "one more vote" is substantially more likely to be appointed mayor, but this does not happen when the most voted was female and the second was male, suggesting the presence of some voter bias. We also show that, in a subsample of municipalities with low bias — proxied by having had a female mayor in the past — the difference between the two electoral systems disappears.

Cover -- Title -- Copyright -- Contents -- Chapter 1 -- Approaching and Understanding Bias -- Chapter 2 -- Navigating the Misinformation Age -- Chapter 3 -- How to Win the Fight Against Bias -- Chapter 4 -- Putting Your Skills into Action -- Glossary -- Further Information -- Bibliography -- Index -- About the Author -- Back Cover.

AbstractThe handling of potential stakeholder bias distinguishes evaluation theorists from one another and from practitioners.

This paper introduces a socio-technical typology of bias in data-driven machine learning and artificial intelligence systems. The typology is linked to the conceptualisations of legal anti-discrimination regulations, so that the concept of structural inequality-and, therefore, of undesirable bias-is defined accordingly. By analysing the controversial Austrian "AMS algorithm" as a case study as well as examples in the contexts of face detection, risk assessment and health care management, this paper defines the following three types of bias: firstly, purely technical bias as a systematic deviation of the datafied version of a phenomenon from reality; secondly, socio-technical bias as a systematic deviation due to structural inequalities, which must be strictly distinguished from, thirdly, societal bias, which depicts-correctly-the structural inequalities that prevail in society. This paper argues that a clear distinction must be made between different concepts of bias in such systems in order to analytically assess these systems and, subsequently, inform political action.

This Article takes a fresh approach to Chevron deference. Chevron requires judges to defer to agency interpretations of statutes and justifies this on a theory of statutory authorization for agencies. This Article, however, points to a pair of constitutional questions about the role of judges – questions that have not yet been adequately asked, let alone answered. One question concerns independent judgment. Judges have a constitutional office or duty of independent judgment, under which they must exercise their own independent judgment about what the law is. Accordingly, when they defer to agency interpretations of the law, it must be asked whether they are violating their duty to exercise their own independent judgment. A second question concerns systematic bias. Under the Fifth Amendment right to the due process of law, judges cannot engage in systematic bias. Therefore, when they defer to agency interpretations of the law, it must be asked whether they are engaging in systematic bias in favor of the government and against Americans, thus denying them the due process of law. These constitutional questions require judges to reconsider Chevron. Rather than dwell on the usual statutory question about authorization, judges (including lower court judges) need to focus on the constitutional questions about their own role.

Cover -- Contents -- Foreword -- Introduction: Fairness, Politics, and the American Media -- Point: Journalists Are Out of Touch with America -- Counterpoint: Journalists' Views Do Not AffectT heir Reporting -- Point: The Media Have a Liberal Bias -- Counterpoint: Claims of Liberal Media Bias Are Exaggerated -- Point: Concentrated Media Ownership Harms the Public -- Counterpoint: The Media Are Healthier Than Ever -- Conclusion: Reforming the Media -- Appendix Beginning Legal Research -- Elements of the Argument -- Notes -- Resources -- Picture Credits -- Index.