Apprendre de l'audit qualité dans les établissements d'enseignement supérieur : un outil pour améliorer la gestion des ressources humaines, le cas Omanaise (Learning From Quality Auditing in Higher Education Institutions: A Tool To Improve Human Resources Management, the Case of Oman)
Bibliographic record
Abstract
French abstract: Le developpement de la societe, les competences des etudiants et l’offre d’un niveau d’education respectueux sont devenus en partie lies a l’efficacite des ressources humaines des etablissements de l’enseignement superieur. L'evaluation de la qualite de la gestion des ressources humaines par les etablissements d'enseignement superieur est une composante majeure du processus d'accreditation. Les recherches consacrees a l'etude de l'importance de la gestion strategique des RH dans les etablissements d'enseignement superieur sont abondantes, mais celles qui mesurent l’efficacite de la GRH sont rares. La majorite des recherches sur l’evaluation de la qualite etaient axees sur la mesure de l’impact organisationnel ou educatif, mais peu d’entre elles ont etudie les sources de cet impact et presque aucune d’entre elles n’a etudie l’impact de l’evaluation de la qualite sur la gestion strategique des ressources humaines dans un environnement comparatif. Au cours de notre recherche, nous avons essaye de demontrer une correlation positive entre la publication des rapports d’audit qualite et la production de resultats positifs en termes de GRH. Nous avons ete en mesure de notifier un certain impact positif dans certains domaines lies au soutien du personnel. Les progres constates sont partiels, certaines sous-zones d’evaluation ayant ete severement critiquees et plusieurs recommandations d’amelioration ayant ete emises a cet egard. Nos resultats empiriques offrent divers indices pour la mise en œuvre efficace d'un processus qualite et d'une culture basees sur les lecons tirees des experiences, des forces et des faiblesses d'autres entites controlees en termes de gestion strategique des ressources humaines. English abstract: The development of the society, the students' skills and the offer of a respectful level of education have become in part linked to the efficiency of human resources in higher education institutions. Evaluation of the quality of human resource management by higher education institutions is a major component of the accreditation process. There is an abundance of research exploring the importance of strategic HR management in higher education institutions, but little research that measures the effectiveness of HRM. The majority of research on quality assessment has focused on measuring organizational or educational impact, but few have investigated the sources of this impact and almost none have studied the impact of quality assessment on strategic HR management in a comparative environment. In the course of our research, we have tried to demonstrate a positive correlation between the publication of quality audit reports and the production of positive HRM results. We were able to report some positive impact in certain areas related to staff support. The progress noted is partial, with some sub-areas of assessment having been severely criticized and several recommendations for improvement having been made in this regard. Our empirical results provide various clues for the effective implementation of a quality process and culture based on lessons learned from the experiences, strengths and weaknesses of others; and entities controlled in terms of strategic resource management human.
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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 | 0.031 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".