Is Knowledge Contagious? Diffusion of Violence-Risk-Reporting Practices Across Clinicians’ Professional Networks
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
The knowledge–practice gap remains a challenge in many fields. Health research has shown that professional networks influence various aspects of patient care, including diffusion of innovative practices. In the current study, we examined the potential utility of professional networks to spread the use of violence-risk-assessment tools in forensic psychiatric settings. A total of 6,664 reports, written by 708 clinicians, were used to examine the effect of clinicians’ use of risk-assessment tools on subsequent reports by other clinicians with whom they share patients. Results show that professional networks serve as an important channel for the spread of assessment practices. Simulation of a continuing education program showed that targeting more influential clinicians in the network could be 3 times more efficient at disseminating best practices than randomly training clinicians. Decision-makers may consider using professional networks to identify and train influential clinicians to maximize diffusion of the use of risk-assessment instruments.
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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 | 0.012 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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