Implementing Community-Engaged Participatory Research Methods in a Study of Cree Women’s Wellness: Describing Recruitment Processes and Outcomes
Bibliographic record
Abstract
Background: In 2017, the Sohkitehew Group was funded to undertake research to identify wellness strategies adopted by mature women as they age in the rural Cree community of Maskwacis, Alberta. We describe our recruitment processes and outcomes for events from July 2017 to June 2018, the first phase of this research. Methodology: Data gathered from minutes of 36 Sohkitehew Working Group and two Elders Advisory Committee meetings were used to identify recruitment strategies, event characteristics and recruitment outcomes for two large community events and three Sharing Circles. Results:1. Recruitment strategies: Strategies were similar for community events and Sharing Circles: event posters were displayed throughout Maskwacis, and advertisements were broadcast by Hawk Radio and appeared in Band newsletters.2. Event Characteristics: Settings included a large community gymnasium for large events, and smaller community venues in different Bands for Sharing Circles. Traditional/cultural protocols were addressed by smudging meeting spaces, inviting community Elders to attend all events, and saying prayers. Healthy lunches were provided.3. Event attendance: The two larger community events attracted 96, and 37 participants, respectively. Sharing Circle attendance ranged from 8 to 23 participants. Conclusion: Recruitment strategies succeeded for the Sohkitehew events in Maskwacis. Prior trusting and respectful relationships with the community established over several years provided a firm basis for this research. Successful recruitment efforts required time, planning, flexibility, and careful attention to culture and tradition to meet objectives to attract participants. Similar strategies may be successful in other rural Indigenous communities if tailored for the specific needs and expectations of individual communities.
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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 | 0.170 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".