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Record W2737047132 · doi:10.1177/1548051817712876

The Role of Workplace Popularity: Links to Employee Characteristics and Supervisor-Rated Outcomes

2017· article· en· W2737047132 on OpenAlexaff
Rebecca Garden, Xiaoxiao Hu, Yujie Zhan, Feng Wei

Bibliographic record

VenueJournal of Leadership & Organizational Studies · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPopularitySupervisorPsychologyAntecedent (behavioral psychology)Social psychologyPoliticsTask (project management)Public relationsApplied psychologyPolitical scienceManagement

Abstract

fetched live from OpenAlex

Popularity in the workplace is relatively unexplored but has multiple potential applications in organizations. This field study uses data collected from 223 supervisor–subordinate dyads at various organizations in China to examine core self-evaluation (CSE) as an antecedent of employee popularity, the ability of political skill and work engagement to predict popularity above and beyond CSE, and the moderating roles of political skill and work engagement on the relationship between CSE and popularity. The current research also extends potential effects of workplace popularity beyond coworker-related outcomes to supervisor trust and task performance ratings for popular employees. Results showed that political skill and work engagement relate to popularity above and beyond CSE and moderate the CSE–popularity relationship. Employees’ popularity is also positively associated with supervisor trust and task performance ratings. 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 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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.037
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
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 head0.065
GPT teacher head0.291
Teacher spread0.226 · 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 teacher head, 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

Citations10
Published2017
Admission routes1
Has abstractyes

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