Talking about risk-taking with potentially ‘problematic’ risk-takers: a study of preventive interactions under high uncertainty
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
Drawing upon examples in the realms of crime prevention and public health, this article discusses the interactions between agents involved in preventive strategies and people identified as likely to engage in ‘problematic’ risk-taking in areas where there are frequently high levels of uncertainty. Considering the substance of the interactions between risk assessors and/or risk managers and risk bearers provides ground for challenging common assumptions regarding the relevance of the persistent divide between ‘expert knowledge’ vs. ‘lay beliefs’ and to develop an alternative framework for analysing the judgements of the various stakeholders regarding uncertainty, namely: probabilistic, clinical and experiential knowledge of risky situations. In turn, analysing the extent to which these sources of knowledge are interrelated and used is indicative of the extent to which uncertainty is acknowledged - or denied - through prevention, once it has been turned into interactions that involve risk assessors/managers and risk-takers.
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 | 0.010 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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