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Oakes Bay 1: A Preliminary Reconstruction of a Labrador Inuit Seal Hunting Economy in the Context of Climate Change

2010· article· en· W2032622651 on OpenAlexaffabout
James Woollett

Bibliographic record

VenueGeografisk Tidsskrift-Danish Journal of Geography · 2010
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBaySubsistence agricultureGeographyContext (archaeology)Subsistence economySpring (device)Climate changePhysical geographyArchaeologyOceanographyGeology

Abstract

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Abstract Geografisk Tidsskrift—Danish Journal of Geography 110(2):245–259, 2010 This paper presents results of recent archaeological research at the site of Oakes Bay 1 (HeCg-08), on Dog Island, Labrador, dated from the late 17th to late 18th century. Analyses of faunal remains provide a means of reconstructing the site's subsistence economy. The site's inhabitants practiced a very consistent mode of hunting throughout this time period, depending heavily on adult ringed seals taken on the fast ice in winter and spring. Juvenile ringed seals, taken at the ice edge in the spring were a secondary resource. A lack of evidence for the hunting of harp seals in the fall and of ringed seal pups in late spring suggests that the site had a relatively short season of occupation. The consistent pattern of hunting through time suggests that the impacts of climatic variability on Inuit subsistence in the Nain region were relatively limited, moderated by their capacity for mobility on the sea ice rather than by whole scale changes in hunting practices and species choice. The Oakes Bay 1 site presents an example of a different subsistence economy than that seen at other recently examined sites in Labrador, suggesting that the impacts of the so-called Little Ice Age were not global or uniform. Keywords: Labrador Inuitclimate change impactszooarchaeologyseasonalityage of death studiesOakes Bay 1

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)0.004
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 score0.105
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
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 head0.019
GPT teacher head0.296
Teacher spread0.277 · 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

Citations25
Published2010
Admission routes2
Has abstractyes

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