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Pre-contact Diets of Indigenous Subarctic Peoples of North America

2016· book-chapter· en· W2522101428 on OpenAlexaff
Emőke J. E. Szathmáry

Bibliographic record

VenueOxford University Press eBooks · 2016
Typebook-chapter
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsSubarctic climateIndigenousGeographyFood contact materialsDiversity (politics)PrehistoryEcologyBiologyArchaeologyPolitical scienceFood scienceLaw

Abstract

fetched live from OpenAlex

Abstract This chapter focuses on the diets of indigenous peoples of the North American Subarctic before European contact, reconstructing the dietary past using several lines of evidence. These include the climate and environment of the North American Subarctic Culture Area, its animal and plant resources, the prehistory of its indigenous inhabitants, and information on food resources obtained during the contact-traditional phase of their history. For hunting-gathering peoples the maintenance of dietary adequacy requires the consumption of balanced diets. That balance depends on the existence of diversity in the plant and animal species on which people depend, and which must be available in sufficient quantities to meet their needs. Accordingly, the chapter focuses on the wild foods that were likely to have been consumed aboriginally, describes the composition of pre-contact diets, and comments on the nutrition and health of Subarctic peoples as perceived at the time of contact.

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)0.000
metaresearch head score (Gemma)0.000
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: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.001

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 head0.026
GPT teacher head0.265
Teacher spread0.239 · 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
Published2016
Admission routes1
Has abstractyes

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