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Record W4377004889 · doi:10.7202/1095887ar

L’effet de la rémunération monétaire et non monétaire sur la détresse psychologique : le cas du salaire, des augmentations de salaire et de la reconnaissance du superviseur

2023· article· fr· W4377004889 on OpenAlexaff
Julie Cloutier, Jacques Gascon

Bibliographic record

VenueHumain et Organisation · 2023
Typearticle
Languagefr
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsEconomicsHumanitiesPolitical scienceWelfare economicsPhilosophy

Abstract

fetched live from OpenAlex

L’objectif de cette étude consiste à déterminer dans quelle mesure et de quelle manière les types de rétributions monétaires et non monétaires influencent le niveau de détresse psychologique. Les données ont été collectées auprès de 320 employés provenant d’établissements du secteur des finances et des assurances. Un test de médiation selon la méthode « bootstrap » a été effectué. Les résultats montrent que les perceptions d’équité des rétributions (sécurité d’emploi, salaire, reconnaissance, augmentation de salaire basée sur le rendement) agissent sur la détresse psychologique parce qu’elles signalent aux employés leur valeur (perception de justice distributive). De plus, les rétributions basées sur le rendement agissent également à travers l’interprétation que font les employés des objectifs à atteindre (ex. valeur et estime ; risques d’échec).

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)0.006
metaresearch head score (Gemma)0.020
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.026
GPT teacher head0.403
Teacher spread0.377 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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