Les politiques de gestion de l'absence des entreprises et leurs impacts sur l'absentéisme au travail
Bibliographic record
Abstract
Résumé L'absence au travail est une préoccupation constante chez tous les dirigeants d'entreprise. C'est pourquoi plusieurs entreprises ont conçu et appliqué différentes politiques de gestion de l'absence. Cet article étudie l'influence de deux types de politiques de gestion de l'absence sur l'absentéisme des travailleurs, è savoir (a) les politiques de rémunération des absences et (b) les politiques relatives aux congés de maladie non utilisés. Pour ce faire, une banque de données recueillies auprès de 555 travailleurs de la grande région montréalaise est utilisée. Les résultats d'analyses hiérarchiques vont dans le sens de notre hypothèse générate de travail, hypothèse selon laquelle les politiques de gestion de l'absence ont un impact significatif sur l'absentéisme au travail. Plus spécifiquement, les travailleurs qui reçoivent une rémunération lors de leur absence vont s'absenterplus souvent que ceux qui n'en reçoivent pas. De plus, parmi les trois politiques relatives aux congés de maladie, les résultats indiquent que la politique d'accumulation des congés de maladie est celle qui encourage le plus d'absence, suivie par la politique de rémunération des congés de maladie. C'est la politique de perte des congés de maladie non utilisés qui occasionne le moins d'absence parmi les trois politiques. Cet article se termine par une réflexion sur les implications des résultats. Abstract Work absenteeism is a constant concern for all managers. Over time, many business organizations have designed and implemented various policies to manage work absenteeism. This study investigates the correlation between two types of policies to manage work absenteeism and the level of worker absenteeism, namely: (a) policies for the payment of absences and (b) policies pertaining to unexpended sick leave. The data bank used was created with information provided by 555 workers in the Greater Montréal area. The results of hierarchical‐regression analyses support our general work assumption, that is, policies to manage work absenteeism have a significant impact on work absenteeism. In other words, workers who receive payments during their leaves are likely to be absent more often than those who do not receive any. Furthermore, results show that the policy of accumulating sick leave results in the highest rate of absenteeism, followed by the policy of receiving payment for sick leave. Of the three policies discussed, we noticed that the policy of losing unexpended sick leave results in the least number of absences. We conclude our study with a discussion on the implications of the results.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".