An inclusive and diverse governance structure of the strategy for patient-oriented research (SPOR) Evidence Alliance
Bibliographic record
Abstract
The Strategy for Patient Oriented Research (SPOR) Evidence Alliance is a research initiative in Canada whose mission is to promote the synthesis, dissemination, and integration of research results into health care and public health decision-making and clinical practice. The aim of this paper is to ( i) outline the governance and committee structure of the SPOR Evidence Alliance, ( ii) outline the procedures for patient and health system decision-maker engagement, and ( iii) present the capacity-building strategy for governance members. The governance structure includes the following six standing committees: the International Advisory Committee, Steering Committee, Executive Committee, Knowledge Translation Committee, Partnerships Committee, and Training and Capacity Development Committee. The guiding principles embrace inclusiveness, support, mutual respect, transparency, and co-building. There are currently 64 committee members across the six committees, 13 patient and public partners, 8 health system decision-makers, 7 research trainees, and 36 researchers. A multi-disciplinary and diverse group of people in Canada are represented from all regions and at various levels of training in knowledge generation, exchange, and translation. This collaborative model makes the SPOR Evidence Alliance strong and sustainable by leveraging the knowledge, lived experiences, expertise, skills, and networks among its 342 members and 12 principal investigators.
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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 | 0.192 | 0.133 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.012 | 0.013 |
| Scholarly communication | 0.022 | 0.008 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".