School Principals’ Stressors and Coping Strategies : A Comparative Study Between Finland and Canada
Bibliographic record
Abstract
The aim of this study was to investigate the stressors and coping strategies of school principals in Finland and Canada with the help of three research questions: what are the causes of the job stressors?, what strategies do school principals use to try to cope with these stressors?, and what specific support do school principals need, or what changes should occur to support them? Using the results of this qualitative study, the main job stressors, coping strategies, and support mechanisms were identified. The research data included both the diaries (N=8) and individual interviews (N=8) of principals. Regarding the analysis, after the theory-guided phase focusing on the diaries, the data-based phase focused on both diaries and interviews. The research findings showed that the main stressors in both Finland and Canada were workload and insufficient time to complete tasks, and constant interruptions. Canadian principals worked significantly more than their Finnish counterparts. School violence and disagreements also caused job stress for principals. In Finland, only verbal disagreements were reported, not physical violence, except for one case of bullying. With regards to coping strategies, the data showed that principals took care of their physical and mental health through a variety of activities. They also knew how to prioritize and were proactive in many cases. Finnish principals frequently delegated work, an uncommon practice in Canada. Regarding support, the lack or non-replacement of human resources seemed to be a major issue in both countries. Nevertheless, the data showed that in both countries, principals were well supported by the network of people around them. Keywords: School principal, stressor, coping strategy, support, comparative study
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.019 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".