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Record W4296712978 · doi:10.1163/15718069-bja10074

Understanding Justice

2022· article· en· W4296712978 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Negotiation · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Philosophy and Ethics
Canadian institutionsBalsillie School of International AffairsUniversity of Waterloo
Fundersnot available
KeywordsEconomic JusticeNegotiationNatural (archaeology)SociologyEpistemologyLaw and economicsLawPolitical scienceSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstract People often disagree about what counts as “just” in a particular case. Such disagreement is natural and understandable once we realize that people commonly bring to the concept of justice different understandings of what makes something just or unjust, interpret general principles differently in specific circumstances, and/or fail to see eye to eye on appropriate ways of resolving justice disputes. But in all cases, disagreement about what is just logically requires that the parties share an understanding of what it is that they are disagreeing about. Similarly, any analysis of the role justice might play in a particular domain – here, negotiation – requires a shared understanding of what it is that is playing the role in question. The purpose of this article is to articulate and justify a shared understanding of the concept of justice that facilitates both the understanding and resolution of justice disputes.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.993
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.281
GPT teacher head0.393
Teacher spread0.112 · 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