Mesurer différemment l’identification à l’organisation : résultats d’une série d’études sur l’adaptation française et la validation d’un instrument graphique
Bibliographic record
Abstract
Divisée en trois études complémentaires, cette recherche porte sur l’adaptation française de l’instrument graphique d’identification organisationnelle de Shamir et Kark (2004). Une première étude montre que l’instrument graphique converge avec un instrument multi-items de l’Identification organisationnelle, et ce, en plus d’établir sa fiabilité test-retest. Une seconde étude montre que les instruments graphique et multi-items entretiennent des patrons corrélationnels semblables avec l’engagement affectif, le soutien organisationnel perçu et l’insécurité d’emploi. Une troisième étude fait le décloisonnement de l’instrument graphique selon différents foyers d’identification (c.-à-d., l’organisation, le superviseur, l’emploi). Pris ensemble, ces résultats suggèrent un bon fonctionnement de la version française de l’instrument graphique.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.094 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".