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Record W4385457014 · doi:10.30861/9781407314891

The Toquaht Archaeological Project: Research at T'ukw'aa, a Nuu-chah-nulth village and defensive site in Barkley Sound, Western Vancouver Island

2023· book· en· W4385457014 on OpenAlexaboutno aff
Alan D. McMillan, Gregory G. Monks, Denis E. St. Claire

Bibliographic record

VenueBAR Publishing eBooks · 2023
Typebook
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSound (geography)ArchaeologyGeographyEthnographyOceanographyGeology

Abstract

fetched live from OpenAlex

The Toquaht Archaeological Project was led by the authors in cooperation with the Toquaht First Nation, one of the Nuu-chah-nulth peoples of western Vancouver Island, British Columbia. The Nuu-chah-nulth formerly lived in large villages of plank-covered houses facing the sea, relying on a wide variety of fish species and marine mammals, including large whales. This volume presents research results from T'ukw'aa, the ancient village in Barkley Sound from which the modern Toquaht derive their name. This location, occupied for over 1,000 years, includes a defensive headland, or “fortress,” that provided a lookout location and place of refuge during hostilities. Ethnographic and ethnohistoric descriptions of Toquaht life are followed by discussion of archaeological research at T'ukw'aa to examine life prior to contact with Europeans and immediately after. All excavated materials, including faunal remains and artifacts, are described and assessed, providing insights into past lifeways in this outer-coast community.

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 score0.484
Threshold uncertainty score0.973

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0070.002
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0150.002

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 head0.111
GPT teacher head0.394
Teacher spread0.283 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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