Examining and Addressing Men's Boating Safety Behaviours in Inuvik, Northwest Territories
Bibliographic record
Abstract
Injuries are one of the leading causes of death for individuals in Canada. Most injuries are predictable and preventable events that may be reduced by health promotion and injury prevention strategies. In particular, boating fatalities are a leading cause of injury death for men, particularly Aboriginal men, in northern Canada. Despite decades of water safety campaigns, Aboriginal men remain overrepresented in boating fatality statistics. Elevated rates of boating fatalities for Aboriginal men in northern Canada indicate that current water safety messages and initiatives may not be reaching those most vulnerable to boating incidents. My thesis, which is written in the publishable paper format and is comprised of two papers, investigates Aboriginal men’s boating incidents in Inuvik, Northwest Territories, Canada. In paper one, I use a community-based participatory research methodology informed by postcolonial feminist theory to investigate the risk factors that Aboriginal male residents identified as contributing to boating incidents in Inuvik, Northwest Territories. Together, we found that sex and gender, age, place, and lack of boating safety education are the most prominent risk factors for boating incidents. In paper two, I argue that community members are key holders of local knowledge and their expertise should thus be drawn upon by academic researchers and health programmers for the co-creation of injury prevention programs. In it, I provide an overview of the process that led to the co-creation of a boating education poster campaign in Inuvik. Together, the two papers in this thesis demonstrate that community-based strategies should be employed to address health inequities in boating incidents faced by Aboriginal men in the Northwest Territories.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".