Are we on the same page? Comparing the perceptions of professionals on overall sexual offending risk
Bibliographic record
Abstract
The current study will be looking at overall sexual risk perceptions of professionals who assess and treat sexual offenders. The participants will be members of the Association for the Treatment of Sexual Abusers (ATSA), who will be asked to complete an online survey comprised of a vignette and a questionnaire. The vignette will describe a person who has offended sexually and will include one of three levels of risk (i.e., low, moderate, high). The questionnaire will also be comprised of basic questions about the participant, their role in conducting risk assessments, and their attitudes and individual characteristics. The survey will attempt to address three separate questions. First, we will be looking at how different risk categories are perceived. Second, participants will be asked about the intensity of treatment that they believe should be assigned to a given level of risk. Finally, the survey will examine the relationship between their perceptions and their political attitudes, general views on sexual offenders, and punitive attitudes of the participants. The findings from this study may provide insight into treatment providers’ perceptions of risk and how this may influence predictions of reoffending and treatment decisions, such as allocation of services. Their perceptions may also be associated with specific characteristics and traits, which will also be examined and may identify reason for these perceptions. Discipline: Psychology Honours Faculty Mentor: Dr. Sandy Jung
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".