Psychological study of the convict’s personality depending on the number of criminal records
Bibliographic record
Abstract
The article is devoted to an empirical analysis of diagnostics problems study of personality traits among convicts serving sentences in prison.On the basis of the obtained data, the psychological characteristics of negative personal traits of convicts in the aspect of psychological support of educational impact on them are determined.The author of the article used the «Dark triad» questionnaire developed in 2002 by Canadian researchers Delra Paulhus and Kevin Williams. This questionnaire is aimed at measuring the subclinical personality traits included in the so-called «Dark triad»: narcissism, psychopathy and machiavellianism. This method has shown its effectiveness in the diagnostic work of prison psychologists. The key task of the study was to identify statistically significant differences in the groups of convicts serving their first sentence and those who had previously been convicted several times.The study involved 200 convicts. Comparing the differences in the groups of convicts, the author notes their specificity. In particular, high levels of dark constructs were identified from a group of repeatedly serving sentences in places of liberty deprivation.The presence of pronounced negative personality traits form a single global index of «dark personality». Scales of the «Dark triad» that reflect the negative personal core allow to quickly get the necessary indices and identify the mechanisms of convicts’ functioning serving sentences in correctional institutions.Prison psychologists need to take into account the high rates of negative constructs in order to implement psychological support measures for convicts throughout the entire period of serving their sentence.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".