Developer/Adapter Method: A Community-Based Approach to Improve Health in Indigenous Communities
Bibliographic record
Abstract
The purpose of this paper is to provide a narrative of our experience with community-driven change using our “Developer/Adapter” research method in Northern Ontario, Canada, so it can be explored in other First Nations contexts. The goal of our currently funded research is to identify community solutions and knowledge and implement community-developed interventions to better support older Indigenous persons, especially those in rural and remote communities, to “age in place” and remain independent in the community through timely access to relevant care. Our Developer/Adapter research method was developed in response to the community-identified need for self-determination to overcome the limitations of traditional Western approaches and effectively plan and execute change in Indigenous communities. Our approach commits to supporting a self- determining voice for Indigenous people and working collaboratively to develop wholistic care interventions. We believe this approach can generate compelling data for policy and practice change in both Canada and Australia.
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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 | 0.040 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.011 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".