Exploration des liens entre la communication de labels employeurs dans les annonces de recrutement, le mode de gouvernance et l’attractivité des organisations aux yeux des candidats
Bibliographic record
Abstract
Résumé Afin d’attirer les talents, de plus en plus d’entreprises cherchent à obtenir des labels employeurs. Cette étude expérimentale examine si les liens entre la communication de labels ( Great Place to Work et/ou Ecologique) dans les annonces de recrutement et l’attractivité des organisations aux yeux des candidats sont 1) modérés par le mode de gouvernance de l’organisation (coopérative vs cotée en bourse) et 2) médiatisés par leurs perceptions du prestige de l’organisation et de leur adéquation personne-organisation. L’étude menée auprès de 320 répondants montre que, quel que soit le mode de gouvernance, la communication du label Great Place to Work améliore l’attractivité de l’organisation aux yeux des candidats, via leurs perceptions plus élevées du prestige de cette dernière et de leur adéquation avec elle. Parmi les entreprises cotées en bourse, celles qui communiquent un label Great Place to Work sont perçues comme plus attractives que celles qui affichent un label Ecologique.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".