Bibliographic record
Abstract
The injury death rate among Aboriginal infants/children is almost four times higher than the Canadian population – Aboriginal toddlers are 15 times more likely to drown than other children. Why? Because many communities are close to open water that are used for livelihood, transportation and recreation and have less access to swimming lessons/lifesaving training. The need to provide training in swimming and injury prevention has been identified as necessary by Aboriginal communities. Goals ▶ develop a culture of water safety ▶ engage/foster collaboration among families, communities and the injury prevention sector ▶ establish linkages between the Canadian Red Cross, Safe Kids Canada and Aboriginal communities. Canadian Red Cross and Safe Kids Canada consulted with Aboriginal communities to develop a shared responsibility approach and create effective messaging/teaching strategies that used the learn to swim/first aid programmes and drowning prevention resources. The learn to swim/first aid programmes target specific age group to address the causes of injury for each. Education programmes teach children how to swim and parents how to prevent drowning, injuries in their home and their community. Year One ▶ communities were identified ▶ learn to swim programme was developed in consultation with parents, extended families, elders and other community members and in an Aboriginal friendly learning environment ▶ over 100 children and parents were trained in swimming and injury prevention. Year Two ▶ two Aboriginal teens/adults were trained as water safety instructors in six reserves ▶ water safety information starts to become part of a new safety culture ▶ reserves have new knowledge and instructors provide annual lessons and support parents to make environments safer ▶ increased access to first aid training and trained people who assist others.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".