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Record W4385127996 · doi:10.1016/j.jas.2023.105824

The role of salmon fishing in the adoption of pottery technology in subarctic Alaska

2023· article· en· W4385127996 on OpenAlexaff
Marjolein Admiraal, Peter Jordan, Helen M. Talbot, Manon Bondetti, Alejandro Serna, Karine Taché, Matthew von Tersch, Jessica Hendy, Krista McGrath, Oliver E. Craig, Alexandre Lucquin

Bibliographic record

VenueJournal of Archaeological Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversité Laval
FundersRijksuniversiteit GroningenArts and Humanities Research CouncilNational Park ServiceSmithsonian Institution
KeywordsPotteryArchaeologyGeographySubarctic climateFishingResource (disambiguation)EcologyBiology

Abstract

fetched live from OpenAlex

Ceramic technology makes an abrupt appearance in the New World Arctic at circa 2800 cal BP. While there is general consensus that the ultimate source of these Alaskan pottery traditions lay in continental NE Asia, the motivations for the adoption of pottery in Alaska have remained unclear. Through organic residue analysis we investigated the function of Norton pottery in Southwest Alaska, and the extent to which its function changed in later periods under the increasing northern influence of Thule culture in the region (from ca. 1000 cal BP). Our results show clear evidence of aquatic resource processing in all pottery vessels. Regional variability due to environmental and ecological differences are apparent in the pottery. The majority of Norton pottery was from inland riverine locations and the function of this early pottery was to process anadromous fish, with only limited evidence of other resources. After 1000 cal BP more sites appear on the coast, and while pottery technology changes dramatically at this time, this is not as clear in pottery function which remains aimed at local abundant aquatic resources. We hypothesize that pottery was adopted into Alaska as part of a riverine adaptation and suggest that targeted human exploitation of large riverine systems may have facilitated its expansion into Southwest Alaska. Furthermore, we suggest that this pattern might extend back into Siberia where Alaskan pottery originates.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.009
GPT teacher head0.244
Teacher spread0.235 · 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.

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

Citations8
Published2023
Admission routes1
Has abstractyes

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