Prehending Addiction: Alcohol and Other Drug Professionals’ Encounters With “New” Addictions
Bibliographic record
Abstract
This article investigates the ways new forms of addiction are encountered by professionals working in the area of alcohol and other drugs. Combining interviews with policymakers, service providers, and peer advocates in three countries (Australia, Canada, and Sweden), and Mike Michael's utilization of the notion of prehension for science communication, we track the notions of addiction, drugs, and subjectivity that emerge when alcohol and other drug professionals encounter what Fraser, Moore and Keane call the addicting of nonsubstance-related practices. The analysis has three parts: constituting addiction unity, questioning addiction unity, and conflicting logics of addicting processes. We argue that specific articulations of drugs and health and specific health professional and addiction subjects are made anew in these encounters. These notions of drugs, health, and subjectivity shape how alcohol and other drug professionals engage with substance-related addictions. In concluding, we consider the implications of new addictions for professional practice.
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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 | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.035 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".