He oranga tō te wai: Māori Pedagogies - A Culturally Responsive View of Aquatic Education and Drowning Prevention in Aotearoa
Bibliographic record
Abstract
Drowning is a leading cause of accidental death and hospitalisation among Māori in Aotearoa. Drowning reports (Water Safety New Zealand, 2010, 2016, 2019) indicate Māori are over-represented in drowning compared to non-Māori, and on average account for up to a quarter of all drowning fatalities each year. Māori male aged 15-44 years and Māori children under five are most at risk of drowning (WSNZ, 2018, 2). A recent Aotearoa study on children’s water survival skills suggest changes are needed to improve how children develop fundamental aquatic skills and how teachers can best teach those skills (Button et al., 2017). In particular, the teaching of water safety skills for broader use in the open water environments of Aotearoa. \nMāori pedagogies within physical education, health, and education in the outdoors (Hemara, 2000; Jackson et al, 2016; Phillips, 2018) have demonstrated the benefits of Māori teaching methods that foster positive learning outcomes for Māori. (Bishop & Berryman, 2006, 2009). As such, this research investigated core components of Māori pedagogies that can improve aquatic education for Māori. It sought to validate traditional and contemporary aquatic teachings and water safety practices that Māori exercise as an expression of ira tangata (human development) and their relationship with te ao tūroa (the long-standing world). By means of kaupapa Māori research and the development of a new framework - Tāne Whānau Mārama, this thesis offers valuable insights into the importance of culturally responsive pedagogies in aquatic education that will enhance the health, educational achievements, and well-being of Māori whānau and communities.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 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".