The Concerns of Ontario Elementary School Teachers on School- Based Emergencies and Emergency Preparedness
Bibliographic record
Abstract
The world is in a constant state of change and evolution, bringing with it new hazards and risks. Every inhabited place on earth is exposed to various hazards and risks, be it natural or human made. People are beginning to discover that places which were historically deemed to be ‘safe’ places, such as schools, are also susceptible to risks and hazards. In recent years, school-based emergencies, such as school shootings, have received a large amount of media coverage and exacerbated public fear. Parents and guardians place their trust in the school system to keep their child(s) safe, as children spend a large portion of their day at school. School teachers are responsible for the safety of the children in their classroom and throughout the school, which begs the question: Are elementary school teachers concerned with school-based emergencies, and do they believe there is enough preparation and education on the subject for both staff and students? This study uses interviews of elementary teachers and examines the major concerns/themes, which are as follows: Lockdown/intruder situations, lack of training, students with disabilities, evacuation procedures, first aid training, and access to emergency information. The interviewed teachers expressed the most concern with unpredictable situations such as an intruder/lockdown, the challenges surrounding students with disabilities, and the fact that it is not mandatory for all teachers to be first aid certified. Children are considered a vulnerable population, and thus require that school emergency plans are regularly exercised and the gaps in the plans filled.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".