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Record W4240472568 · doi:10.1086/700086

Notes on Contributors

2018· article· en· W4240472568 on OpenAlexaboutno aff

Bibliographic record

VenueEthics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Economic JusticeSociologyLawPolitical scienceMedia studiesHistory

Abstract

fetched live from OpenAlex

Previous article FreeNotes on ContributorsPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinked InRedditEmailQR Code SectionsMoreDerrick Darby is professor of philosophy at the University of Michigan, Ann Arbor. He is the author of Rights, Race, and Recognition (2009). His most recent book, coauthored by John L. Rury, is The Color of Mind: Why the Origins of the Achievement Gap Matter for Justice (2018). [email protected]Helen Frowe is professor of practical philosophy and Wallenberg Academy Fellow at Stockholm University, where she directs the Stockholm Centre for the Ethics of War and Peace. Her work focuses on permissible harming, particularly harming in self-defense and war. Her books include Defensive Killing (2014) and The Ethics of War and Peace: An Introduction (2011). She is coinvestigator on the AHRC-funded project Heritage in War.Anders Herlitz is a researcher at the Institute for Futures Studies in Stockholm, Sweden, and a visiting scientist at Harvard T.H. Chan School of Public Health. His research focuses on comparability problems and justified choice, in particular in the context of population ethics. He is the PI of the project Good and Just Allocation of Health-Related Resources and a member of the research program Climate Ethics and Future Generations in Stockholm. [email protected]Jennifer M. Morton is an associate professor of philosophy at the City College of New York and Graduate Center–CUNY and senior fellow at the Center for Ethics and Education at the University of Wisconsin–Madison. She received her PhD from Stanford University. Her research interests include philosophy of action, practical reasoning, philosophy of education, and moral and political philosophy more generally. Currently, she is completing a book concerning the ethical costs faced by first-generation students in the path of upward mobility, to be published by Princeton University Press. [email protected]Jacob M. Nebel is a PhD candidate in philosophy at New York University and, starting fall 2019, assistant professor of philosophy at the University of Southern California.Shmuel Nili is an assistant professor of political science at Northwestern University and a research fellow at the Australian National University’s School of Philosophy. [email protected]Sarah K. Paul is an associate professor of philosophy at the University of Wisconsin–Madison. She received her PhD from Stanford University. Her research interests include the philosophy of action, practical reasoning, and self-knowledge. She is currently completing an introductory book on the philosophy of action, to be published by Routledge Press. [email protected]Johanna Thoma received her PhD from the University of Toronto and is an assistant professor at the Department of Philosophy, Logic and Scientific Method at the London School of Economics. Her main research interests are in practical rationality, decision and game theory, contractarian ethics, and philosophy of economics. [email protected]Patrick Tomlin is a reader in philosophy at the University of Warwick. [email protected] Previous article DetailsFiguresReferencesCited by Ethics Volume 129, Number 2January 2019 Article DOIhttps://doi.org/10.1086/700086 © 2018 by The University of Chicago. All rights reserved.PDF download Crossref reports no articles citing this article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.717
Threshold uncertainty score0.403

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0050.001
Scholarly communication0.0080.006
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.7170.600

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.178
GPT teacher head0.440
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2018
Admission routes1
Has abstractyes

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