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Justice and Negotiation

2015· review· en· W2102111981 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

VenueAnnual Review of Psychology · 2015
Typereview
Languageen
FieldSocial Sciences
TopicConflict Management and Negotiation
Canadian institutionsInternational Institute for Sustainable Development
FundersVetenskapsrådet
KeywordsNegotiationEconomic JusticeProcedural justiceDistributive justicePsychologyRelation (database)Process (computing)Social psychologyField (mathematics)EpistemologySociologyPolitical scienceLawSocial scienceComputer science

Abstract

fetched live from OpenAlex

This review article examines the literature regarding the role played by principles of justice in negotiation. Laboratory experiments and high-stakes negotiations reveal that justice is a complex concept, both in relation to attaining just outcomes and to establishing just processes. We focus on how justice preferences guide the process and outcome of negotiated exchanges. Focusing primarily on the two types of principles that have received the most attention, distributive justice (outcomes of negotiation) and procedural justice (process of negotiation), we introduce the topic by reviewing the most relevant experimental and field or archival research on the roles played by these justice principles in negotiation. A discussion of the methods used in these studies precedes a review organized in terms of a framework that highlights the concept of negotiating stages. We also develop hypotheses based on the existing literature to point the way forward for further research on this topic.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.924
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.159
GPT teacher head0.527
Teacher spread0.368 · 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