From knowledge to action: protocol for a mixed-methods evaluation of First Nations-led knowledge mobilisation on prenatal opioid exposure
Bibliographic record
Abstract
INTRODUCTION: First Nations communities in Canada are disproportionately impacted by prenatal opioid exposure (POE) and neonatal abstinence syndrome (NAS). In response, we developed a research partnership with 13 First Nations communities in Ontario. Phase I of the research project, initiated in 2018, included the development of mixed-methods reports on the impact of POE for each community. This protocol outlines the evaluation of phase II, during which nine communities individually co-designed and implemented community-specific knowledge mobilisation (KMb) plans informed by findings from phase I. The evaluation aims to assess advisory working group engagement, KMb implementation and perceived community-level impacts. METHODS AND ANALYSIS: This mixed-methods evaluation integrates survey and qualitative data to assess First Nations-led KMb products and activities. The Public and Patient Engagement Evaluation Tool, a validated survey instrument, will be administered to advisory group members and analysed descriptively. Focus groups and interviews will be conducted to explore advisory working group members' experiences and analysed using phenomenological methods. Qualitative findings will be mapped to the Engage with Impact framework to assess outcomes across engagement domains. ETHICS AND DISSEMINATION: Ethics approval has been granted by Vancouver Island University. All community contacts and advisory working group members will provide informed consent prior to data collection. Phase II activities are governed by formal community agreements. In alignment with First Nations Principles of OCAP (Ownership, Control, Access and Possession), First Nations community partners retain ownership of their KMb products and are actively involved in the design, implementation and dissemination of the project evaluation. Results will be shared through peer-reviewed publications, community reports and knowledge-sharing events.
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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 | 0.150 | 0.112 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.114 | 0.021 |
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".