Academic stress and burnout among primary school trainee teachers in the Rabat-Sale-Kenitra region
Bibliographic record
Abstract
During the training phase, the trainee teacher seems to be more and more confronted with discomfort and stress, due to the accumulation of demands and obligations. Many of them are mostly unable to take it any longer, which makes them vulnerable to the burnout risk. This research aims to study the academic burnout of trainee teachers at the “Centre Régional des Métiers de l’Education et de la Formation “(CRMEF) of the Rabat-Sale-Kenitra region during 2019/2020. Four hundred and fifty trainee teachers responded to a self-questionnaire comprising the Maslach Burnout Inventory-Student Survey (MBI-SS) scale in its French version, as well as certain stress factors. In agreement with the literature, more than 60% of teachers show moderate and high levels of academic exhaustion, the main likely stressors presented are financial instability, and training overload. Many trainee teachers cannot cope with the burnout syndrome, which conducts to stress and absenteeism during the training, we hope that this study will lead to some practical solutions to prevent and reduce the risk of academic burnout.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".