The Open Arms Day Centre as a Pou Whirinaki and Key Space of Care within the Conduct of Māori Homeless Lifeworlds in Whangārei, Aotearoa, New Zealand
Bibliographic record
Abstract
Homelessness has re-emerged as a significant issue in Aotearoa, New Zealand (Aotearoa/NZ) in recent decades, with Māori (Indigenous peoples of New Zealand) being impacted disproportionately due to ongoing processes of colonisation and impoverishment. Whether living on the streets of an urban centre, small city, or rural district, the lifeworlds of homeless people are frequently textured by social, material, and spatial exclusions, uncertainties, insecurities, and stigma. This article explores how the Open Arms Day Centre (OADC), a drop-in day centre for homeless people in Whangārei (a small city in Northland), functions as a dependable Pou Whirinaki (pillar of strength and support) in the everyday lives of Māori experiencing homelessness. Employing a Māori-centred, case-based approach, we explored the experiences of a small group of local service users, volunteers, and staff through interviews, photographic exercises, and regular casual conversations. This culturally informed mode of inquiry resulted in a deeper understanding of the OADC’s operation as what health geographers have also referred to as a space of care. Such spaces offer those frequenting them opportunities for respite, inclusion, belonging, and routine. They become Pou Whirinaki through enactments of Māori relational values and practices that foster a sense of ontological security, cultural continuity, and shared humanity
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.014 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| 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".