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Record W4413337764 · doi:10.1002/ajhb.70123

Contributions of Roy J. Shephard to the Study of Circumpolar Human Biology and Health

2025· article· en· W4413337764 on OpenAlexaboutno aff
William R. Leonard, Peter T. Katzmarzyk

Bibliographic record

VenueAmerican Journal of Human Biology · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsCircumpolar starHuman healthHuman biologyArcticIndigenousEnvironmental ethicsSociologyBiologyEcologyAnthropologyMedicineEnvironmental healthOceanography

Abstract

fetched live from OpenAlex

More than any other scholar in our field, Professor Roy J. Shephard's research has shaped and transformed our understanding of the biology and health of circumpolar populations. His long-term research among the Inuit of Igloolik, Canada has provided the field of human biology with foundational insights into how human populations adapt to arctic climates, and how the transition to a market-oriented lifestyle erodes fitness and metabolic health. Shephard was the prime architect of early research done in the Canadian Arctic as part of the Human Adaptability Program (HAP) of the International Biological Programme (IBP) in the 1960s and early 1970s. After the original IBP studies, Shephard and collaborator Andris Rode continued their research in Igloolik through the early 1990s. This long-term research provided some of the first clear evidence on how the process of acculturation and lifestyle change erodes physical development and metabolic health among Indigenous populations of the north. This paper provides an overview of the major findings and insights from Roy Shephard and colleagues' research in Igloolik and highlights how these contributions are shaping ongoing research on the biology and health of circumpolar populations.

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)0.010
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation 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: Other · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.021
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0050.008
Scholarly communication0.0050.004
Open science0.0010.004
Research integrity0.0020.012
Insufficient payload (model declined to judge)0.0030.001

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 head0.044
GPT teacher head0.476
Teacher spread0.432 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2025
Admission routes1
Has abstractyes

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