In search of ethnic New Zealanders Social Policy Journal of New ZealandzIssue 36zAugust 2009 46 IN SEARCH OF ETHNIC NEW ZEALANDERS: NATIONAL NAMING IN THE 2006 CENSUS
Bibliographic record
Abstract
In the 2006 census the number of people reporting New Zealander as their ethnic group increased five-fold, making it the third most frequent response behind New Zealand European and Māori. The magnitude of the increase was surprising, but followed similar surges in national naming in the Canadian and Australian censuses. In this paper we ask: Who chooses to ethnically identify in the name of the nation and why? In so doing we emphasise the constructed nature of ethnicity and ethnic groups, and the political context within which ethnic identification decisions are made. Our analysis suggests the New Zealander incline was a phenomenon driven primarily by multi-generational New Zealanders who formerly identified as European. We discuss some reasons for why the national identifier appears to have selective appeal as an ethnic label, and reflect on how this may change in coming years.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.002 |
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".