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Learning the Tools of Survival in the Thule and Dorset Cultures of Arctic Canada

2018· book· en· W2807449247 on OpenAlexaffabout
Robert W. Park

Bibliographic record

VenueOxford University Press eBooks · 2018
Typebook
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsCanadian Heritage
Fundersnot available
KeywordsPrehistoryArcticGeographyPermafrostArchaeologyThe arcticEthnologyEcologyHistoryOceanographyBiologyGeology

Abstract

fetched live from OpenAlex

The Arctic part of the North American continent has seen some of the most fascinating and demanding human adaptations anywhere, culminating in those of the Inuit who live there today. This region is characterized by persistence of cold (long winters and short cool summers), permafrost (year-round frozen ground), large seasonal differences in the amount of sunlight, few or no trees, and a minimum of plant foods directly consumable by humans. To survive in this environment the Inuit peoples and their predecessors, of necessity, relied on technology and on animal resources to a greater extent than recent hunter-gatherer populations anywhere else in the world. This chapter explores the ethnographic and archaeological records of these peoples and this region to study the nature of childhood in prehistoric hunter-gatherer 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)0.001
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: Empirical
Teacher disagreement score0.040
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0260.017
Scholarly communication0.0090.002
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.034
GPT teacher head0.278
Teacher spread0.244 · 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

Citations1
Published2018
Admission routes2
Has abstractyes

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