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Record W609460571 · doi:10.71781/24237

Culture organisationnelle et supervision abusive

2013· dissertation· fr· W609460571 on OpenAlexfundaboutno aff
Christine Adangnito

Bibliographic record

VenueOpen MIND · 2013
Typedissertation
Languagefr
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsnot available
FundersUniversité de Montréal
KeywordsHumanitiesSociologyAbusive relationshipAbusive supervisionPolitical sciencePsychologySocial psychologyPhilosophyPoison controlHuman factors and ergonomicsDomestic violenceMedicine

Abstract

fetched live from OpenAlex

L’objectif principal de ce mémoire est d’identifier les antécédents organisationnels de la supervision abusive. Alors, un modèle intégrant la culture organisationnelle a été élaboré. Les données primaires recueillies par l’Équipe de Recherche sur le Travail et la Santé Mentale (l’ERTSM) auprès de 2162 employés de 63 établissements au Québec de septembre 2009 à mai 2012 ont permis de tester nos hypothèses. Les analyses multiniveaux réalisées corroborent une relation significative entre la culture organisationnelle et la supervision abusive. Les résultats ont montré que la culture de performance est positivement reliée à la supervision abusive contrairement à la culture de relations sociales. Aussi, ces analyses révèlent que certains subordonnés seraient plus enclins à rapporter de la supervision abusive que d´autres. Enfin, d’autres caractéristiques organisationnelles comme la taille de l’établissement pourraient être associées à la supervision abusive.

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)0.005
metaresearch head score (Gemma)0.015
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 score0.153
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0030.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
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 head0.021
GPT teacher head0.284
Teacher spread0.263 · 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

Citations0
Published2013
Admission routes2
Has abstractyes

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