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Record W1509332585 · doi:10.7202/1025716ar

Inuit and modern hunter-gatherer subsistence

2014· article· en· W1509332585 on OpenAlexaffvenueabout
George W. Wenzel

Bibliographic record

VenueÉtudes/Inuit/Studies · 2014
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMcGill University
Fundersnot available
KeywordsSubsistence agricultureHunter-gathererLivelihoodSubsistence economyEthnologyAnthropologySociologyGeographyHistoryArchaeologyAgriculture

Abstract

fetched live from OpenAlex

Some two decades ago, Asen Balikci (1989) and David Riches (1990) questioned whether research on Inuit, despite production of a voluminous literature, had made any contribution to theoretical issues in anthropology. On their heels, Burch (1994) asked very much the same about Hunter-Gatherer Studies. The thesis of the present paper is that research on Inuit economy has, in fact, contributed importantly to a rethinking of the shape and content of subsistence. Once described as encompassing the most basic economic activities, it is now understood as a cultural adaptation. This has import because few hunter-gatherer societies can be portrayed as they were at the time of theMan the Huntersymposium (Lee and DeVore 1968). Rather, today, hunter-gatherers, from the Arctic to Australia, experience near-constant contact with market economies and a reality in which money plays a critical part in their livelihoods. It is in this regard that research on Inuit, as noted by Sahlins (1999), has conceptually contributed both to Hunter-Gatherer Studies and to anthropology.

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)0.002
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 score0.863
Threshold uncertainty score0.273

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.005
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.086
GPT teacher head0.398
Teacher spread0.312 · 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

Citations29
Published2014
Admission routes3
Has abstractyes

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