Engaging Stakeholders in Review and Recommendations for Models of Outcome Monitoring for Substance Abuse Treatment
Bibliographic record
Abstract
We present an example of a collaborative process designed to review models of outcome monitoring for substance abuse services, with a view to assessing the feasibility of different approaches in Ontario, Canada. A conceptual framework that describes the parameters of an outcome monitoring system and four models of outcome monitoring were identified. Consultations were held with stakeholders (managers, directors, researchers, clinicians, and governmental representatives) about the types of information they would like to obtain from an outcome monitoring system. Our process is useful as a model for collaborative research with respect to performance measurement. The study's implications and limitations are noted.
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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 | 0.727 | 0.739 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.024 | 0.019 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.033 | 0.040 |
| Open science | 0.017 | 0.018 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 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".