Meeting Professional Competencies through Specialized Distance Education: The McMaster University Addiction Studies Program
Bibliographic record
Abstract
Historically, addiction has been an area in which Canadian social workers have received limited formal education. This reality led to the development of 18 core technical competencies through the auspices of the Canadian Centre on Substance Abuse in 2006. A survey of Canadian schools and faculties of social work found that social work students might obtain a grounding in many of these competencies, however, there was no certainty of this. An option now for those interested in becoming more proficient in this field of addiction is a specialized distance education program developed by McMaster University in Hamilton, Ontario. Along with meeting the majority of the core competencies, there are several other attributes that make this program unique. It offers 27 distinct addiction-specific course options at both an introductory and an advanced level; has continuous enrollment allowing students to begin a course at the beginning of any month; has no minimum course load requirement; and meets the academic requirements for optional certification through the Canadian Addiction Counselors Certification Federation. In a nation like Canada, with a small population spread across a large geographic area, the Addiction Studies Program may serve as a template for offering specialized distance education to enhance professional competencies and thus better prepare social workers to serve community needs.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".