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Research funding through third-party financing is of considerable importance for the German science system. The funds of the German Research Foundation (DFG) serve as the central focus due to the high reputation of the foundation. However,…
(No abstract for this journals: article commences: ) Fairness is a key issue in the careers of astronomers. I examine here the anecdota l suggestion that "you're more likely to get time if you're on the TAC", using public and published data…
We study the problem of selecting the top-k candidates from a pool of applicants, where each candidate is associated with a score indicating his/her aptitude. Depending on the specific scenario, such as job search or college admissions,…
Rankings of people and items are at the heart of selection-making, match-making, and recommender systems, ranging from employment sites to sharing economy platforms. As ranking positions influence the amount of attention the ranked subjects…
The design of research grants has been hypothesized to be a useful tool for influencing researchers and their science. We test this by conducting two thought experiments in a nationally representative survey of academic researchers. First,…
Recent studies conducted in different scientific disciplines have concluded that researchers belonging to some socio-cultural groups (e.g., women, racialized people) are usually less cited than other researchers belonging to dominating…
A main issue in improving public sector efficiency is to understand to what extent public appointments are based on worker capability, instead of being used to reward political supporters (patronage). I contribute to a recent literature…
A robust body of evidence demonstrates the adverse effects of implicit bias in various contexts--from hiring to health care. The Rooney Rule is an intervention developed to counter implicit bias and has been implemented in the private and…
Research on fairness in machine learning has been recently extended to recommender systems. One of the factors that may impact fairness is bias disparity, the degree to which a group's preferences on various item categories fail to be…
We study the probabilistic assignment of items to platforms that satisfies both group and individual fairness constraints. Each item belongs to specific groups and has a preference ordering over platforms. Each platform enforces group…
New researchers are usually very curious about the recipe that could accelerate the chances of their paper getting accepted in a reputed forum (journal/conference). In search of such a recipe, we investigate the profile and peer review text…
University rankings are increasingly adopted for academic comparison and success quantification, even to establish performance-based criteria for funding assignment. However, rankings are not neutral tools, and their use frequently…
Many important decisions in societies such as school admissions, hiring, or elections are based on the selection of top-ranking individuals from a larger pool of candidates. This process is often subject to biases, which typically manifest…
In this work we consider general facility location and social choice problems, in which sets of agents $\mathcal{A}$ and facilities $\mathcal{F}$ are located in a metric space, and our goal is to assign agents to facilities (as well as…
Machine Learning (ML) algorithms shape our lives. Banks use them to determine if we are good borrowers; IT companies delegate them recruitment decisions; police apply ML for crime-prediction, and judges base their verdicts on ML. However,…
Over the last decade proposal success rates in the fundamental sciences have dropped significantly. Astronomy and related fields funded by NASA and NSF are no exception. Data across agencies show that this is not principally the result of a…
Geographic proximity is acknowledged to be a key factor in research collaborations. Specifically, it can work as a possible substitute for institutional proximity. The present study investigates the relevance of the "proximity" effect for…
Setbacks are an integral part of a scientific career, yet little is known about whether an early-career setback may augment or hamper an individual's future career impact. Here we examine junior scientists applying for U.S. National…
We study the linear contextual bandit problem where an agent has to select one candidate from a pool and each candidate belongs to a sensitive group. In this setting, candidates' rewards may not be directly comparable between groups, for…
Public and private institutions must often allocate scare resources under uncertainty. Banks, for example, extend credit to loan applicants based in part on their estimated likelihood of repaying a loan. But when the quality of information…