Knowledge Translation in a Community-Based Study of the Relations Among Violence Exposure, Post-traumatic Stress and Alcohol Misuse in Mi’kmaq Youth
Bibliographic record
Abstract
In 2004, our research group was invited to continue a research partnership with a Nova Scotian Mi’kmaq community that was concerned about the causes of and interventions for adolescent alcohol misuse in their community. While our previous collaborative research focused on reducing adolescent alcohol misuse by targeting motivations for drinking that were personality specific (see Mushquash, Comeau, & Stweart, 2007), the more recent collaboration sought to investigate the possible relationship between exposure to violence, post-traumatic stress, and alcohol misuse. The present paper outlines the steps involved in gaining community consent, the plan for results sharing, the tangible benefits to the community that have been documented, and future directions and lessons learned. The paper will demonstrate how the principles of Knowledge Translation (CIHR, 2006) provide a framework for this process.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".