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1. Collective Justice: Ex-Combatants and Community Reparations in Colombia

   https://doi.org/10.1093/jhuman/huac030  

   Dixon, Peter ; Firchow, Pamina ( August 2022 , Journal of Human Rights Practice)

   In conflicts involving non-state armed groups, individualized approaches to transitional justice and disarmament, demobilization, and reintegration face significant shortcomings for both victims and ex-combatants. Yet, both transitional justice and disarmament, demobilization, and reintegration have had trouble interrogating the tensions between individualized and collective approaches, focusing more on normative debates over the proper balance than on the actual experiences of communities in transition. This paper seeks to advance this debate through empirical research on the local experience of justice and coexistence amid civilian and ex-combatant communities in Colombia. The authors utilized a unique dataset of ‘everyday’ community-based indicators of coexistence and justice in eight civilian and ex-combatant communities in rural Colombia. Using the country’s web of reparations mechanisms, the paper draws a distinction between ‘state-led’ and ‘community-led’ collective justice and proposes that the latter can speak to both civilian and ex-combatant communities’ priorities and lived experiences—and, ultimately, provide a pathway to coexistence. This would stand in contrast to the Colombian state’s current collective reparations projects by speaking directly to the concerns and priorities of both civilian and ex-combatant communities: on the civilian side, to be compensated directly by those who committed acts of violence; and on the ex-combatant side, tomore »be recognized and accepted as a community. Such a community-led model integrating transitional justice and disarmament, demobilization, and reintegration processes would serve as a pragmatic middle ground between the individual and state-led collective approaches that dominate transitional justice.

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2. The Paradox of Automation as Anti-Bias Intervention

   Ajunwa, Ifeoma ( April 2020 , Cardozo law review)

   A received wisdom is that automated decision-making serves as an anti-bias intervention. The conceit is that removing humans from the decision-making process will also eliminate human bias. The paradox, however, is that in some instances, automated decision-making has served to replicate and amplify bias. With a case study of the algorithmic capture of hiring as heuristic device, this Article provides a taxonomy of problematic features associated with algorithmic decision-making as anti-bias intervention and argues that those features are at odds with the fundamental principle of equal opportunity in employment. To examine these problematic features within the context of algorithmic hiring and to explore potential legal approaches to rectifying them, the Article brings together two streams of legal scholarship: law and technology studies and employment & labor law. Counterintuitively, the Article contends that the framing of algorithmic bias as a technical problem is misguided. Rather, the Article’s central claim is that bias is introduced in the hiring process, in large part, due to an American legal tradition of deference to employers, especially allowing for such nebulous hiring criterion as “cultural fit.” The Article observes the lack of legal frameworks that take into account the emerging technological capabilities of hiring tools whichmore »make it difficult to detect disparate impact. The Article thus argues for a re-thinking of legal frameworks that take into account both the liability of employers and those of the makers of algorithmic hiring systems who, as brokers, owe a fiduciary duty of care. Particularly related to Title VII, the Article proposes that in legal reasoning corollary to extant tort doctrines, an employer’s failure to audit and correct its automated hiring platforms for disparate impact could serve as prima facie evidence of discriminatory intent, leading to the development of the doctrine of discrimination per se. The article also considers other approaches separate from employment law such as establishing consumer legal protections for job applicants that would mandate their access to the dossier of information consulted by automated hiring systems in making the employment decision.« less
3. Mapping scientists’ career trajectories in the survey of doctorate recipients using three statistical methods

   https://doi.org/10.1038/s41598-023-34809-1  

   Edwards, Kathryn Anne ; Acheson-Field, Hannah ; Rennane, Stephanie ; Zaber, Melanie A. ( May 2023 , Scientific Reports)

   This paper investigates to what extent there is a ‘traditional’ career among individuals with a Ph.D. in a science, technology, engineering, or math (STEM) discipline. We use longitudinal data that follows the first 7–9 years of post-conferral employment among scientists who attained their degree in the U.S. between 2000 and 2008. We use three methods to identify a traditional career. The first two emphasize those most commonly observed, with two notions of commonality; the third compares the observed careers with archetypes defined by the academic pipeline. Our analysis includes the use of machine-learning methods to find patterns in careers; this paper is the first to use such methods in this setting. We find that if there is a modal, or traditional, science career, it is in non-academic employment. However, given the diversity of pathways observed, we offer the observation that traditional is a poor descriptor of science careers.
4. Who Profits from Patents? Rent-Sharing at Innovative Firms*

   https://doi.org/10.1093/qje/qjz011  

   Kline, Patrick ; Petkova, Neviana ; Williams, Heidi ; Zidar, Owen ( March 2019 , The Quarterly Journal of Economics)

   Abstract This article analyzes how patent-induced shocks to labor productivity propagate into worker compensation using a new linkage of U.S. patent applications to U.S. business and worker tax records. We infer the causal effects of patent allowances by comparing firms whose patent applications were initially allowed to those whose patent applications were initially rejected. To identify patents that are ex ante valuable, we extrapolate the excess stock return estimates of Kogan et al. (2017) to the full set of accepted and rejected patent applications based on predetermined firm and patent application characteristics. An initial allowance of an ex ante valuable patent generates substantial increases in firm productivity and worker compensation. By contrast, initial allowances of lower ex ante value patents yield no detectable effects on firm outcomes. Patent allowances lead firms to increase employment, but entry wages and workforce composition are insensitive to patent decisions. On average, workers capture roughly 30 cents of every dollar of patent-induced surplus in higher earnings. This share is roughly twice as high among workers present since the year of application. These earnings effects are concentrated among men and workers in the top half of the earnings distribution and are paired with corresponding improvements in workermore »retention among these groups. We interpret these earnings responses as reflecting the capture of economic rents by senior workers, who are most costly for innovative firms to replace.« less
5. Opportunity Unraveled: Private Information and the Missing Markets for Financing Human Capital

   Herbst, Daniel ; Hendren, Nathaniel ( September 2021 , NBER working paper series)

   Investing in college carries high returns but comes with considerable risk. Financial products like equity contracts can mitigate this risk, yet college is typically financed through non-dischargeable, government-backed student loans. This paper argues that adverse selection has unraveled private markets for college-financing contracts that mitigate risk. We use survey data on students’ expected post-college outcomes to estimate their knowledge about future outcomes and quantify the threat of adverse selection in markets for equity contracts and several state-contingent debt contracts. We find students hold significant private knowledge of their future earnings, academic persistence, employment, and loan repayment likelihood, beyond what is captured by observable characteristics. Our empirical results imply that a typical college-goer must expect to pay back $1.64 in present value for every $1 of equity financing to cover the financier’s costs of covering those who would adversely select their contract. We estimate that college-goers are not willing to accept these terms so that private markets unravel. Nonetheless, our framework quantifies significant welfare gains from government subsidies that would open up these missing markets and partially insure college-going risks.