PRINCIPAL BEHAVIOURS DURING SCHOOL EMERGENCIES
Bibliographic record
Abstract
School emergencies are thankfully rare, but there is no escaping the reality that they do take place. Schools have a duty to ensure that students are safe. School boards, principals and teachers all play a role in helping reduce the number of school emergencies, but, as research has found, they also play a role in helping guide and lead during threatening situations that are unforeseeable, infrequent and unavoidable. This study looks at school emergencies through the lenses of school board emergency plans and of those who actually experience school emergencies head on - the school principal. This study used two methods of inquiry. The first method involved a two-part literature review. Academic works pertaining to school emergency preparedness and training were first analyzed. Second, emergency plans from eight Ontario school boards were analyzed. The second method of inquiry involved twenty semi-structured interviews with retired and current principals and probed how they viewed emergencies and how they felt their role changed when an emergency took place in their school. Overall, 152 unique emergencies incidents were documented from school board emergency plans and from the recorded interviews of the principals. Often, the experiences of principals did not coincide with official school board protocols. The gap in planning presents unique challenges that resonate with how principals are trained and prepared for emergencies and with how they must gather personal expertise in order to effectively deal with situations for which their school board may not have planned.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".