Bibliographic record
Abstract
This paper was written from the point of view of a real crisis worker belong to a Crisis Intervention Program in Canada. My main goal was to transfer these specific and sensitive knowledge and protocols about assessment and intervention of a suicidal individual to the hypothetic crisis services from Romania. The paper reproduced the real steps of an algorithm followed by a crisis worker having to respond to a suicidal crisis: (i) contact, (ii) communication, (iii) assessment protocol and instruments, (iv) risk and protective factors, (v) general and particular issues of the interviewing with a suicidal individual, and (vi) intervention methods. The suicidal subject is taken specifically into account in various situations: unsuccessful suicidal attempt, presence of a suicidal ideation, formulation of a suicidal plan, and possession of the resources to fulfill a suicidal plan. Intervention protocol for a suicidal individual is portrayed as a 25-step logically program ended up with the formulation of a suicidal safety plan, follow-up contacts, referral to other services, and documentation. All these crisis worker’s activities are highly standardized and structured so that he/she will stand up accountable for the job done. Drawing up this paper, the author has creatively incorporated his personal experience working in the crisis programs and the review of a large body of international references.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".