“That's why people don't call 911”: Ending routine police attendance at drug overdoses
Bibliographic record
Abstract
Research has shown that police attendance and the corresponding threat of criminal charges are major deterrents to people seeking emergency medical assistance in the event of an overdose. In response to these barriers, Canada passed the Good Samaritan Drug Overdose Act in 2017, providing immunity from prosecution for simple drug possession to overdose victims or bystanders who phone 911. In theory, this should make people more comfortable seeking emergency supports, but in practice our research found that many remain hesitant because police continue to be routinely dispatched to the overdose site. Based on focus groups and surveys with 109 people who use drugs across Ontario, Canada, our findings show that the vast majority of participants have negative interactions with police, which discourages them from seeking medical assistance at future overdose incidents. Almost all questioned the necessity of dispatching law enforcement to a health emergency that requires medical intervention. As such, this commentary draws on the study's qualitative data to argue that ending routine police attendance at drug overdoses in Ontario would remove a major barrier to calling 911, and thus prevent the further, unnecessary loss of life in the ongoing overdose crisis.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.019 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".