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Record W3103901906 · doi:10.7819/rbgn.v16i52.1782

Percepção de Controlabilidade e Equidade da Avaliação de Desempenho

2014· article· pt· W3103901906 on OpenAlexaff

Bibliographic record

VenueReview of Business Management · 2014
Typearticle
Languagept
FieldDecision Sciences
TopicBusiness and Management Studies
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsDecentralizationControllabilityContext (archaeology)PerceptionOutcome (game theory)Affect (linguistics)

Abstract

fetched live from OpenAlex

We investigated the effects of environmentaluncertainty, decentralization of decisions rights,and the use of subjective performance measures onmanagers’ perceptions of outcome controllabilityand performance evaluation fairness. Basedon a survey of 339 middle- and upper- levelmanagers, our results suggest that environmentaluncertainty adversely affects perceptions ofoutcome controllability and that this effectis not moderated by the decentralization ofdecision rights. Our results also show a positiveassociation between perceived controllabilityand performance evaluation fairness. Althoughwe found no direct effect of the use of subjectiveperformance measures on perceived performanceevaluation fairness, it appears to moderate thepositive effect of perceived controllability onfairness. We also show that the positive effectof the use of subjective measures may dependon contextual and job-related factors. Theoverall results underscore the need to considerthe organizational context (environmentaluncertainty and decentralization of decisionrights) to investigate how performance measuresaffect perceived controllability and fairness.Because perceived controllability and fairnessaffect individual attitudes and behaviors withinan organization, our results have importantimplications for the design and use of performanceevaluation systems.

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)0.011
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.824
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.067
GPT teacher head0.362
Teacher spread0.295 · 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.

Study designNot applicable
Domainnot available
GenreMethods

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

Citations1
Published2014
Admission routes1
Has abstractyes

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