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The Influence of Organizational Politics on Performance Appraisal

2009· book-chapter· en· W342497181 on OpenAlexaff
Gary P. Latham

Bibliographic record

VenueOxford University Press eBooks · 2009
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPoliticsAffect (linguistics)PhenomenonInterpersonal communicationPublic relationsSubject (documents)Social psychologyPerformance appraisalPsychologyPolitical scienceManagementEpistemologyEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract Political behaviors in organizations consist of self-serving actions taken by an individual or group. They are directed toward the goal of furthering one's own self-interest without regard for the wellbeing of others in the organization. Such actions are informal and, as part of an organization's culture, regulate interpersonal relationships. The fact that the politics inherent in organizational behavior affect an employee's appraisal was noted more than a quarter of a century ago by behavioral scientists. Nevertheless, there is a paucity of systematic research on this subject. Thus, the purpose of this article is fourfold. First, the phenomenon of organizational politics is described. Second, studies on the relationship between political behavior and appraising employees are reviewed. Third, steps to minimizing its adverse effects on the appraisal of employees are outlined. Finally, a research agenda is suggested.

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)0.011
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.012
GPT teacher head0.196
Teacher spread0.184 · 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

Citations7
Published2009
Admission routes1
Has abstractyes

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