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Record W2015747358 · doi:10.1207/s15327957pspr0704_04

An Analysis of Empirical Research on the Scope of Justice

2003· article· en· W2015747358 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

VenuePersonality and Social Psychology Review · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Intergroup Psychology
Canadian institutionsWestern UniversityBrock University
Fundersnot available
KeywordsScope (computer science)ConceptualizationEconomic JusticeHarmEmpirical researchPsychologyCriminologySocial psychologySociologyPolitical scienceLawEpistemologyComputer science

Abstract

fetched live from OpenAlex

The scope of justice has been defined as the boundary within which justice is perceived to be relevant. The empirical literature on this topic is primarily aimed at predicting when a target will be excluded from the scope of justice and at examining potential consequences of exclusion, from accepting a target's suffering to active harm-doing such as mass internment and genocide. The concept of the scope of justice is interesting and heuristically useful, but there are several problems with the empirical literature that impede its progress. For example, the proposed mediator often has not been measured, or operationalizations of the scope of justice have been confounded with other constructs. Also, although the scope of justice remains one possible explanation for results obtained in various experiments, there are equally compelling alternatives that do not implicate exclusion from the scope of justice. We offer suggestions about how to study scope of justice issues in the future and identify points that need to be clarified regarding the conceptualization of the scope of justice.

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)0.008
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.894
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.471
GPT teacher head0.618
Teacher spread0.147 · 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