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Record W4317802018 · doi:10.1093/whq/whad023

The Search for the First Americans: Science, Power, Politics. By Robert V. Davis Jr.

2023· article· en· W4317802018 on OpenAlexaff
George Nicholas

Bibliographic record

VenueWestern Historical Quarterly · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicAustralian Indigenous Culture and History
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHegemonyIndigenousPoliticsPower (physics)Government (linguistics)Interpretation (philosophy)InterrogationSociologyService (business)EpistemologyPolitical scienceSocial scienceEnvironmental ethicsLawPhilosophyEconomicsEconomy

Abstract

fetched live from OpenAlex

The question of who the First Americans were continues to evolve as new sites are found and dated, sometimes in previously unexplored regions (e.g., the continental shelf), and new technologies employed. Robert Davis offers a fresh take on the extensive and sometimes contradictory literature, on contentious claims, and on different ways of ways of knowing the past. As a non-archaeologist (a Ph.D. in science and technology, and a career in public service with the federal government), he has no vested interest in any particular interpretation. This volume, however, is not a review of the facts, but rather an interrogation of what various beliefs (Indigenous) and lines of evidence (Science) offer—to use Davis’s dichotomy here. He notes “This examination of the search for the First Americans is a case study in the complex relationships between the biological findings of science and the social importance of cultural beliefs” (p. x). This frames his approach, but he states equal interest in the “often fractious relationships across the sciences” and the “hegemonic and often racist assumptions… embedded in how science has been conducted” (p. x). Clearly there is a packed agenda in this volume.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0090.017
Scholarly communication0.0070.008
Open science0.0010.004
Research integrity0.0050.010
Insufficient payload (model declined to judge)0.0030.002

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 head0.032
GPT teacher head0.317
Teacher spread0.286 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2023
Admission routes1
Has abstractyes

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