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Record W7096240792

Rather above than under the common size? Stature and Living Standards in New Zealand 1

2009· article· en· W7096240792 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldArts and Humanities
TopicAutobiographical and Biographical Writing
Canadian institutionsnot available
Fundersnot available
KeywordsInequalityIndigenousPopulationCohortLate 19th centuryQuarter (Canadian coin)Period (music)
DOInot available

Abstract

fetched live from OpenAlex

Abstract: For Europeans and their descendents New Zealand was a relatively healthy environment during the 19th century. New Zealanders were relatively tall. Nevertheless stature declined from the 1870s to the early 1880s cohorts, again from the 1880s to the late 1890s, and from the 1910s to the early 1920s. We hypothesize that the 19th century experience reflects the same pattern of adverse pressure on net nutrition documented for this period in other countries. The failure of stature to rise after 1900 is more surprising as height was beginning to rise in other overseas European populations. The sharp decline for the 1920s cohort probably reflects the abrupt deceleration of the New Zealand economy at that time. Stature differed across occupational groups; farmers and men in higher socio-economic status occupations were taller. The differential between shorter and taller groups increased from the late 19th to the early 20th centuries; rising inequality then is one possible explanation for the failure of population mean stature to rise 1900-1920. There was some tendency for those born into a New Zealand city to be shorter as adults. No systematic differences between New Zealanders of European descent and the indigenous Maori are visible before 1900, although among the post-1900 cohorts the

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.565

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2009
Admission routes1
Has abstractyes

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