Agency Revisited: Addiction Services’ Clients’ Recovery in the Light of the Brain Disease Model of Addiction (BDMA)
Bibliographic record
Abstract
Proponents and critiques of the brain disease model of addiction (BDMA) discuss its benefits and shortcomings in the light of agency. Yet, in this controversy, the experiences of the persons suffering from addiction have so far been widely neglected. This article investigates addiction service's clients’ experiences with their recovery in the light of the BDMA. It asks what role the BDMA plays in the recovery narratives of persons struggling with addiction. Eleven focus groups were conducted with clients of the Centre for Addiction and Mental Health in Toronto, Canada. The interview protocol consisted of direct questions and discussion stimuli concerning the BDMA. The transcripts were analyzed by a thematic analysis. Participants both approved and disapproved the BDMA. The recovery narratives demonstrate how agency can be constructed without autonomy. Whereas the BDMA questions the agency of persons suffering from addiction in denying them autonomy, it helped as a symbolic resource in including the contradictive experiences with addiction into an authentic biography. This study thus urges addiction research to make use of agency in its entirety and take both, autonomy and biography, into account.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.025 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.008 |
| 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".