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Record W2104340542 · doi:10.1111/ehr.12099

Health, height, and the household at the turn of the twentieth century

2015· article· en· W2104340542 on OpenAlexafffund
Roy E. Bailey, Timothy J. Hatton, Kris Inwood

Bibliographic record

VenueThe Economic History Review · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsUniversity of Guelph
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsFunctional illiteracyCrowdingLocalityCensusDemographic economicsGeographyDemographySocioeconomicsEconomicsSociologyPolitical sciencePsychology

Abstract

fetched live from OpenAlex

This article examines the health and height of men born in England and Wales in the 1890s who enlisted in the army at the time of the First World War, using a sample of recruits from the army service records. These are linked to their childhood circumstances as observed in the 1901 census. Econometric results indicate that height on enlistment was positively related to socio‐economic class, and negatively to the number of children in the household in 1901 and the proportion of household members who were earners, as well as to the degree of crowding. Adding the characteristics of the locality has little effect on the household‐level effects. However local conditions were important; in particular the industrial character of the district, local housing conditions, and the female illiteracy rate. These are interpreted as representing the negative effect on height of the local disease environment. The results suggest that changing conditions at both household and locality levels contributed to the increase in height and health in the following decades.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.038
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.088
GPT teacher head0.226
Teacher spread0.139 · 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

Citations49
Published2015
Admission routes2
Has abstractyes

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