ISQUA16-2526GOVERNANCE STANDARDS FOR ABORIGINAL HEALTH SERVICES - A COLLABORATIVE JOURNEY
Bibliographic record
Abstract
In an effort to better reflect the context and governance structures of Aboriginal Health Services (AHS) organizations, the Qmentum Governance standards were revised in collaboration with an advisory committee of representatives from the Aboriginal community. The new Governance for Aboriginal Health Services standards were developed in 2015 and released to clients in January 2016. Developing standards is a rigorous process designed to ensure that standards are measureable, relevant, evidence-informed and serve as effective tools for transforming knowledge to practice. This development process began with a scoping literature review, followed by focus groups to gather contextual knowledge related to governance structures in AHS organizations. The revision was further supported through convening an expert advisory committee with national representation from Aboriginal communities and surveyors to build consensus around the standards and language in a collaborative way. Next, a national consultation was held to obtain broad feedback on the revised standards prior to finalization. This feedback was incorporated and a final validation was performed with the expert advisory committee, prior to releasing the new standards in January 2016.
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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 | 0.417 | 0.321 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.026 | 0.013 |
| Open science | 0.012 | 0.024 |
| Research integrity | 0.019 | 0.023 |
| Insufficient payload (model declined to judge) | 0.019 | 0.010 |
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".