Increasing Response Rates on Face-to-Face Surveys with Indigenous Communities in Canada: Lessons from Pictou Landing
Bibliographic record
Abstract
BACKGROUND: Designing an effective survey for gathering primary health data using a community-based participatory research (CBPR) approach in Indigenous communities in Canada has its challenges. Yet, the Pictou Landing First Nation (PFLN) Native Women's Group (NWG) and academic research partners achieved a 59% response rate. OBJECTIVES: To share lessons learned with both campus and community-based research teams engaged in CBPR involving Indigenous communities on the process of team development, and particularly survey development and execution, as well as the factors that led to a reliable and valid household level environmental health survey that achieved a 59% response rate. METHODS: Multiple debriefings conducted over the course of the 12-month data collection period allowed us to modify our protocol to fit with community oscillations. RESULTS/LESSONS LEARNED: Unique aspects of CBPR allowed for the development of a culturally appropriate survey protocol and culturally relevant variables that reflected the concerns of the NWG, and presenting preliminary data to the community also encouraged community buy-in to participate. CONCLUSIONS: Sharing lessons learned in this project are intended to have positive implications for future CBPR projects wanting to collect primary health survey data involving Indigenous communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".