Denial and its relationship with treatment perceptions among sex offenders
Bibliographic record
Abstract
We examined the relationship between denial/minimization and treatment perceptions using multiple measures of each construct in a sample of 185 adult male sex offenders. Denial/minimization was measured with the Comprehensive Inventory of Denial—Sex Offender version (CID-SO), Sex Offender Acceptance of Responsibility Scales (SOARS), and an item from a risk assessment measure (Sexual Violence Risk-20; SVR-20). Treatment perceptions were measured with the treatment readiness scale of the Multiphasic Sex Inventory (MSI and MSI-II) and the treatment rejection scale of the Personality Assessment Inventory (PAI). Most aspects of denial and minimization had significant moderate to strong associations with more negative perceptions of treatment. Questions about the distinctiveness versus overlap between measures of denial/minimization and treatment perceptions notwithstanding, our findings are consistent with conceptualizations in past research and practice that greater denial/minimization is associated with lower motivation for treatment. Rather than excluding deniers from treatment, additional efforts are required to engage higher risk sex offenders exhibiting denial and minimization.
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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 | 0.008 |
| 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 | 0.001 |
| 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".