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Record W4283782962 · doi:10.1177/10596011221112232

How and When Can Employees with Status Motivation Attain Their Status in a Team? The Roles of Ingratiation, OCBI, and Procedural Justice Climate

2022· article· en· W4283782962 on OpenAlexaff
Chunjiang Yang, Yashuo Chen, Jijun Gao

Bibliographic record

VenueGroup & Organization Management · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Manitoba
FundersNational Natural Science Foundation of China
KeywordsPsychologySocial psychologyOperationalizationSocial statusProcedural justiceSocial exchange theoryDominance (genetics)SociologyPerceptionSocial science

Abstract

fetched live from OpenAlex

Despite research having identified two major routes to status: dominance and competence, both routes seem inadequate to capture the “whole picture” of how people get ahead in organizations. Building on social exchange theory and social status literature, we identify two novel paths and their important boundary conditions by which employees with status motivation can achieve status. Specifically, we propose that employees with status motivation obtain status (operationalized as other-perceived status and promotability) by engaging in ingratiation toward their supervisors and organizational citizenship behavior directed toward individuals. In addition, these relationships are weakened in teams where the procedural justice climate is high. Results from four studies conducted in China and the United States, which consist of three experiments (Study 1: N = 240; Study 2: N = 180; Study 4: N = 309) and one field study of 427 employees from 74 teams (Study 3), provide support for most of the propositions we proposed. The theoretical and practical implications of these findings are discussed.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.187
Teacher spread0.180 · 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 designObservational
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

Citations20
Published2022
Admission routes1
Has abstractyes

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