Analysis of the real activity of school principals in Morocco: A case study of four primary schools in the Rahmna region
Bibliographic record
Abstract
School principals play a key role in improving student outcomes by mobilizing the school community, fostering teacher motivation and capacity, and influencing the climate and work environment [1,2,3,4]. While the role of principals is crucial, their duties have evolved, and they face increased complexity and demands [5]. Therefore, there is a need to rethink initial training to increase their level of preparation. However, it is not possible to talk about a training program without a minimum analysis of the tasks it involves and the actual activities that characterize it [6]. This research proposes to analyse in detail and in depth the real activity of a sample of four Moroccan primary school principals and to collect, in an ethnographic approach, information on their work and on their school results and academic success. We will work with school principals from the region of Rhamna, who have been in their position for less than three years and who were randomly selected among the respondents to a previous national quantitative survey. We will analyse the actual practices and tasks of the principals based on self-confrontation interviews conducted activity traces (anthropological approach) but also based on 360 videos recorded during the main working sessions between each principal and other actors of the school community. In the field of school administration studies in Morocco (and in Africa), there is no experience with this relatively recent perspective. Thus, we hope that the results of this research will contribute to the construction of a theoretical and methodological framework, which will subsequently become a potential reference for the design of a training program for school principals.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".