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Record W2038151244 · doi:10.1177/2041386610376255

An employee-centered model of organizational justice and social responsibility

2011· article· en· W2038151244 on OpenAlexfundno aff
Deborah E. Rupp

Bibliographic record

VenueOrganizational Psychology Review · 2011
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Studies
Canadian institutionsnot available
FundersUniversity of TorontoEconomic and Social Research CouncilAssociation for Psychological Science
KeywordsOrganizational justiceDignityPsychologySocial psychologyPerceptionElement (criminal law)Orientation (vector space)CognitionEconomic JusticeOrganizational commitmentPublic relationsPolitical scienceLaw

Abstract

fetched live from OpenAlex

This paper reviews recent research within the area of organizational justice. It argues that a key element of the employee experience is the formation of perceptions about how both the self and others are treated by organizational stakeholders, as well as the level of dignity and respect bestowed by the organization to external groups. Employees, therefore, look in, around, and out, in order to comprehend their working experiences, and depend on these judgments to navigate the organizational milieu. A full understanding of justice phenomena requires consideration of individual differences; contextual influences; affective, cognitive, and social processes; as well as a person-centric orientation that allows for both time and memory to influence the social construction of worker phenomena.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.005
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0020.014
Scholarly communication0.0050.004
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.090
GPT teacher head0.321
Teacher spread0.231 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations275
Published2011
Admission routes1
Has abstractyes

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