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Record W2059818376 · doi:10.1080/1081602x.2015.1006653

Physical growth and ethnic inequality in New Zealand prisons, 1840–1975

2015· article· en· W2059818376 on OpenAlexaff
Kris Inwood, Les Oxley, Evan Roberts

Bibliographic record

VenueThe History of the Family · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsUniversity of Guelph
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentMarsden Fund
KeywordsDemographyEthnic groupPrisonPopulationInequalityFertilityGeographySociologyPolitical scienceCriminologyLaw

Abstract

fetched live from OpenAlex

The British colonization of New Zealand after 1840 was marked by an unusual concern compared to other settler colonies to incorporate the indigenous Māori population into the new society. But despite a continuing political rhetoric of protection and sovereignty, Māori have historically had lower living standards and, since the 1920s, higher rates of incarceration than European-descended New Zealanders (Pākehā). In this article, the authors examine differences between Māori and Pākehā over 130 years using prison records. Aggregate data from the Ministry of Justice shows long-term change and differences in incarceration rates. Using a data set of all extant registers of men entering New Zealand prisons, the authors show change over time in convictions and in height. The adult statures of Māori and Pākehā were similar for men born before 1900, but marked differences emerged among cohorts born during the twentieth century. By the Second World War, the gap in adult stature widened to around 3 cm, before narrowing for men born after the Second World War. Periods of divergence in stature are paralleled by divergence in fertility and indicators of family size, suggesting the possibility that increasing fertility stressed the economic situation of Māori families. The prison evidence suggests that inequalities in ‘net nutrition’ between Māori and Pākehā are long-standing but not unchanging – indeed, they increased for cohorts born in the early twentieth century. A subset of the data describing adolescents confirms that, among those born after 1945, the ethnic differential was already visible by the age of 16.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.116
GPT teacher head0.248
Teacher spread0.132 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations18
Published2015
Admission routes1
Has abstractyes

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