Addiction Research Centres and the Nurturing of Creativity. Substance abuse research in a modern health care centre: the case of the Centre for Addiction and Mental Health
Bibliographic record
Abstract
The Centre for Addiction and Mental Health is one of the premier centres for research related to substance use and addiction. This research began more than 50 years ago with the Addiction Research Foundation (ARF), an organization that contributed significantly to knowledge about the aetiology, treatment and prevention of substance use, addiction and related harm. After the merger of the ARF with three other institutions in 1998, research on substance use continued, with an additional focus on comorbid substance use and other mental health disorders. In the present paper, we describe the structure of funding and organization and selected current foci of research. We argue for the continuation of this successful model of integrating basic, epidemiological, clinical, health service and prevention research under the roof of a health centre.
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.
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 | 0.093 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.018 | 0.081 |
| Scholarly communication | 0.026 | 0.024 |
| Open science | 0.004 | 0.026 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".