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Record W2030286680 · doi:10.1098/rspb.2015.0211

Does natural selection favour taller stature among the tallest people on earth?

2015· article· en· W2030286680 on OpenAlexaff
Gert Stulp, Louise Barrett, Felix C. Tropf, Melinda Mills

Bibliographic record

VenueProceedings of the Royal Society B Biological Sciences · 2015
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of Lethbridge
FundersNederlandse Organisatie voor Wetenschappelijk Onderzoek
KeywordsDemographyProxy (statistics)Secular variationReproductive successGeographyNatural selectionPopulationSelection (genetic algorithm)StatisticsSociology

Abstract

fetched live from OpenAlex

The Dutch are the tallest people on earth. Over the last 200 years, they have grown 20 cm in height: a rapid rate of increase that points to environmental causes. This secular trend in height is echoed across all Western populations, but came to an end, or at least levelled off, much earlier than in The Netherlands. One possibility, then, is that natural selection acted congruently with these environmentally induced changes to further promote tall stature among the people of the lowlands. Using data from the LifeLines study, which follows a large sample of the population of the north of The Netherlands (n = 94 516), we examined how height was related to measures of reproductive success (as a proxy for fitness). Across three decades (1935-1967), height was consistently related to reproductive output (number of children born and number of surviving children), favouring taller men and average height women. This was despite a later age at first birth for taller individuals. Furthermore, even in this low-mortality population, taller women experienced higher child survival, which contributed positively to their increased reproductive success. Thus, natural selection in addition to good environmental conditions may help explain why the Dutch are so tall.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.433

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 studies0.0010.001
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 head0.029
GPT teacher head0.277
Teacher spread0.248 · 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 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

Citations88
Published2015
Admission routes1
Has abstractyes

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