Assessing normative approaches to communicating violence risk: a national survey of psychologists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
There is growing attention to the importance of violence risk communication, and emerging empirical evidence of how evaluating clinicians who conduct risk assessments communicate their conclusions about the risk of violence toward others. The present study addressed the perceived value of different forms of risk communication through a national survey of practicing psychologists (N = 1,000). Responses were received from a total of 256 participants, who responded to eight vignettes in which three factors relevant to risk communication were systematically varied in a 2 x 2 x 2 within-subjects design, counterbalanced for order: (i) risk model (prediction oriented versus management oriented), (ii) risk level (high risk versus low risk), and (iii) risk factors (static versus dynamic). Participants were asked to rate the value of six styles of risk communication for each of eight vignettes. The most highly valued style of risk communication involved identifying risk factors applicable to the individual, and specifying interventions to reduce risk. These results were consistent with findings from several previous studies in this area, and reflect an emerging trend in preferences for style and context of risk communication of violence.
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.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it