Characteristic features and socio-demographic structure of suicidal behavior of prison staff in the USA and Canada
Bibliographic record
Abstract
В статье рассматривается проблема суицида среди персонала тюрем Соединенных Штатов Америки и Канады на основе анализа актуальных зарубежных исследований и практики оценки суицидальных рисков в пенитенциарной среде. В работе представлены эмпирические данные, отражающие социально-демографические характеристики суицидентов (пол, возраст, образование, семейное положение, расовая и этническая принадлежность) и различные проявления суицидальной активности (мысли, планирование, попытки, завершенный суицид). Анализ суицидального поведения персонала учрежде- ний исполнения уголовных наказаний в рассматриваемых странах проводился с учетом кадровой дифференциации (административные работники, тюремные надзиратели, социальные работники, тюремные капелланы, сотрудники психологической службы) и стажа службы в уголовно-исполнительной системе, что позволило выделить группы суицидального риска, требующие внимания специ- алистов и своевременного психологического сопровождения. The given article deals with the problem of suicide among prison staff in the United States of America and Canada based on an analysis of current foreign researches and practical developments in assessing suicidal risks in the penitentiary environment. The research presents empirical data reflecting the socio-demographic characteristics of suicide victims (gender, age, education, marital status, race and ethnicity) and various manifestations of suicidal activity (thoughts, planning, attempts, completed suicide). The analysis of suicidal behavior of corrections staff in the countries under consideration is carried out taking into account personnel differentiation (administrative workers, prison guards, social workers, prison chaplains, psychological service employees) and years of service in the penitentiary system that has made it possible to identify groups of suicidal risk that require specialist attention and timely psychological support.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".