AN EXPLORATION OF PASIFIKA MULTIGENERATIONAL SOCIAL HOUSING
Bibliographic record
Abstract
This research explores Pasifika multigenerational social housing, defined as the cohabitation of three or more generations. With nearly a quarter of the Pasifika population residing in such extended family situations, the study aims to scrutinize whether the current social housing infrastructure adequately meets their needs. The research, which employed a case study approach, focused on a Pasifika Community Housing provider working predominantly with Pasifika as a cohort and operating large numbers of social housing properties across Auckland. Document analysis and semi-structured interviews with key stakeholders were the main data collection methods. The results suggest a significant misalignment between existing multigenerational housing structures and the actual needs of the Pasifika community. The interview data indicates that the current housing framework falls short of meeting the unique requirements of Pasifika households, hence necessitating a redesign of multigenerational housing to align with the diverse lifestyles and preferences of its occupants. The study highlights the inadequacy of a ‘one size fits all’ approach, emphasizing the need for tailor-made designs reflective of the communities residing in multigenerational housing. In conclusion, policymakers should consider a more inclusive and culturally sensitive approach to the design and implementation of Pasifika multigenerational housing solutions in New Zealand.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".