Suicidal Crisis Negotiations: An Investigation of Situational Characteristics, Hooks and Triggers
Bibliographic record
Abstract
Crisis negotiation teams have previously been described as “gatekeepers” to suicidal individuals, with research showing that these are amongst the most common calls negotiators attend to. Despite this, the situational features of these calls and the communicative dynamics that may lead to the safe resolution of suicidal crises, remain poorly understood. Using a mixed method approach, situational characteristics across four suicidal incident types were examined, and “hooks” and “triggers” that were common in each incident type were identified. The results revealed some consistencies across incident types regarding incident location, and the mental health and substance use histories of subjects. Inconsistencies were observed for communication method used, weapons involved, and resolution details. Numerous hooks and triggers were identified for each incident type. The findings increase our understanding of suicidal crises and have implications for negotiator training (e.g., the features of actual suicidal incidents can inform the content of scenario-based training).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".