Fidélisation des employés de la génération Z dans les Établissements Privés d’Enseignement Secondaire au Cameroun (EPESC)
Bibliographic record
Abstract
More and more young graduates are joining the PSSC. With the technological advances of recent decades, these young people have specific characteristics in the workplace that differ from those of their predecessors. To ensure the long-term future of the organisations employing this emerging workforce, it would be wise to take an interest in their expectations. In order to study these expectations, a qualitative survey was carried out using semi-directive interviews with 64 employees belonging to generation Z working in PSSC and with 12 employers. The data collected was analysed using NVivo12 plus software and the results showed that generation Z employees in the PSSC are highly ambitious, very technophile and have a certain closeness to learners. However, many of them did not join these establishments by vocation. Nevertheless, some have become passionate about teaching. Finally, the main factor in retaining these generation Z employees in PSSC is organisational.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".