Toku toa, he toa rangatira: A qualitative investigation of New Zealand Māori end of life care customs
Bibliographic record
Abstract
Informal end of life caregiving will increase over the next 30 years in line with the anticipated increase in older Māori deaths. Of concern, New Zealand’s neo-colonial trajectory (loss of lands, cultural disenfranchisement, urban migration, ethnic diversity, global diaspora and changing whānau (family, including extended family) compositions) has restricted some indigenous whānau from retaining their end of life care customs. This article reports on a qualitative pilot study on Māori whānau end of life care customs undertaken to explore how those care customs contribute towards strengthening whānau resilience and bereavement. Five whānau, including thirteen individuals from diverse iwi (tribes), took part in one of six face to face interviews. Kaupapa Māori research methods informed the analysis. The findings report a high level of customary caregiving knowledge among older whānau carers as well as a cohesive whānau collective support system for this group. Tribal care customs were handed down via 1) enculturation with tribal principles, processes and practices 2) observing kaumātua processes and practices and 3) being chosen and prepared for a specific care role by kaumātua. Younger participants had strong cultural care values but less customary care knowledge. The pilot concluded the need for a larger systematic qualitative study of Māori tikanga (customs) and kawa (guidelines) as well as the development of participant digital stories to support a free online educational resource to increase understanding among whānau, indigenous communities and the health and palliative care sectors.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 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".