The role of interest‐based facilitation in designing accreditation standards: The Canadian experience
Bibliographic record
Abstract
Abstract This article discusses the design and implementation of a national certification process for family mediators by Family Mediation Canada (FMC) in 1999, as well as findings from data collected during the pilot testing, of the certification process. Debates continue about theoretical orientation, best practices, and thus the feasibility of standards of practice. This article argues that although these debates are vital to disciplinary growth, they deflect attention from areas of fundamental consensus. Professional practice arid certification standards are designed using one of two approaches. The first approach is expert‐driven and evaluative and focuses on differences among practitioners. In this approach, experts evaluate differences and then propose the best model and standards of practice. The second approach is interest‐based and facilitative. It builds on areas of consensus among practitioners. Facilitators use mediation methods to support practitioner self‐empowerment and self‐determination in the design of practice and certification standards. This article argues that adoption of the second approach was the key to the success of the FMC process.
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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 | 0.068 | 0.085 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.017 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".