Self-harming behaviors in prison: a comparison of suicidal processes, self-injurious behaviors, and mixed events
Bibliographic record
Abstract
Self-harming behaviors occurring in prison disproportionately consume resources and cause considerable disruption. To date, theoretical paradigms have explained self-injurious behaviors and suicidal processes either via a continuum or dichotomy of self-harm. This current study examines all documented acts of self-harm (n = 1,158) occurring in South Carolina’s 28 prisons over a 50-month period. We test and find support for a tripartite schema of self-harm; differentiated with regard to suicidal processes, self-injurious behaviors, and a ‘mixed group‘ of self-harming behaviors. These groups of behaviors were distinct with regard to situational variables (i.e. body part targeted, injury severity) as well as institutional responses (i.e., medical treatment needed, employment of suicide protocols). Findings indicate that self-injurious behaviors are likely to result in physical injury and/or hospitalizations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".