Barriers to Calling 9-1-1 during Overdose Emergencies in a Canadian Context
Bibliographic record
Abstract
Research has shown there are notable barriers to calling 9-1-1 during accidental overdose emergencies. Overdose is a significant health and social justice concern, yet Canadian researchers have not explored the existence or prevalence of these systemic obstacles. The current case study examines the barriers to calling 9-1-1 that people face in Southern Ontario when confronted with accidental overdose incidents. The locality of this study is particularly suitable as Wellington County, that is, Waterloo Region and Guelph are socio-demographically similar to Ontario and Canada. Barriers were assessed by surveying individuals that have or currently use drugs (n=291) and are clients of local methadone clinics or outreach services. Data were explored using frequency tables and then compared using crosstabulations. The findings of this case study suggest there are multiple barriers to calling 9-1-1 during accidental drug overdoses. Similar to previous studies, the most common barriers cited were fear of being arrested (53%), breaching probation or parole (30%), and fear of losing custody of children (24%). Lowering the barriers to calling 9-1-1 may help to forge the path necessary to improved health care and access to resources. Ultimately, and most importantly, lives may be saved.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".