More Like this

1. Long‐distance Friends and Collective Action in Fisheries Management

   https://doi.org/10.1111/conl.13073  

   Smith, Kristopher_M; Pisor, Anne_C; Aron, Bertha; Bernard, Kasambo; Fimbo, Paschal; Machano, Haji; Kimesera, Rose; Rubens, Jason; Slade, Lorna; Sobo, Jumanne; et al (December 2024, Conservation Letters)

   ABSTRACT Much received wisdom in the conservation literature is that individual connections across community boundaries undercut natural resource management. However, when multiple communities access the same resource, these long‐distance relationships could generate interdependence and trust to motivate engagement in collective action to manage the resource. To test this, we interviewed 1317 people in 28 fishing villages in Tanzania about their participation in managing open‐access fisheries and their social relationships in each village accessing the fishery. People with more friends in other villages trusted more people in those villages and were more likely to participate in collective action to manage the shared fishery, such as reporting others for destructive fishing practices. These results show that long‐distance relationships may be a useful foundation upon which to build conservation efforts that cross community boundaries and bolster sustainable resource use. 

   more » « less
2. Fairness and Friends

   Arif Khan, Falaah; Manis, Eleni; Stoyanovich, Julia (January 2021, Beyond static papers: Rethinking how we share scientific understanding in ML - ICLR 2021 workshop)

   Recent interest in codifying fairness in Automated Decision Systems (ADS) has resulted in a wide range of formulations of what it means for an algorithm to be “fair.” Most of these propositions are inspired by, but inadequately grounded in, scholarship from political philosophy. This comic aims to correct that deficit. We begin by setting up a working definition of an 'Automated Decision System' (ADS) and explaining 'bias' in outputs of an ADS. We then critically evaluate different definitions of fairness as Equality of Opportunity (EOP) by contrasting their conception in political philosophy (such as Rawls’s fair EOP and formal EOP) with the proposed codification in Fair-ML (such as statistical parity, equality of odds and accuracy) to provide a clearer lens with which to view existing results and to identify future research directions. We use this framing to reinterpret the impossibility results as the incompatibility between different EOP doctrines and demonstrate how political philosophy can provide normative guidance as to which notion of fairness is applicable in which context. We conclude by highlighting justice considerations that the fair-ML literature currently overlooks or underemphasizes, such as Rawls's broader theory of justice, which supplements his EOP principle with a principle guaranteeing equal rights and liberties to all citizens in a free and democratic society. 

   more » « less
3. My Friends and Hadron Physics

   https://doi.org/10.5506/APhysPolB.56.3-A2  

   Eides, MI (March 2025, Acta Physica Polonica B)

   Dmitry Diakonov, Victor Petrov, and Maxim Polyakov were my colleagues and collaborators. Mitya and Vitya were also, and maybe first of all, my close personal friends for many many years. What follows is a mixture of some recollections and a review of our joint works. 

   more » « less
4. Friends in Zn

   Gaubatz, Nicholas; Johnson, Peter (January 2022, International journal of mathematics and computer science)
5. Suggested reviewers: friends or foes?

   https://doi.org/10.1007/s00359-022-01553-2  

   Zupanc, Günther K. (July 2022, Journal of Comparative Physiology A)