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Record W2312275984 · doi:10.7183/0002-7316.77.4.621

Perspectivism, Mortuary Symbolism, and Human-Shark Relationships on the Maritime Peninsula

2012· article· en· W2312275984 on OpenAlexaff
Matthew Betts, Susan Blair, David W. Black

Bibliographic record

VenueAmerican Antiquity · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArchaeology and ancient environmental studies
Canadian institutionsUniversity of New BrunswickMusée de la Civilisation
Fundersnot available
KeywordsGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract Shark teeth are commonly found in mortuary and ritual contexts throughout the Northeast. On the Maritime Peninsula, shark teeth have been identified in mortuary assemblages spanning the Late Archaic through to the Late Woodland periods (ca. 5000 B.P. to 950 B.P.). Beyond the Maritime Peninsula, shark teeth have been recovered from Woodland period contexts ranging from Chesapeake Bay to the Ohio River. Amerindian perspectivism, or cosmológical deixis, provides a framework for understanding the relationship between humans and animals in hunter-gatherer societies. To explore this relationship, we examine engagements between sharks and humans over a period of 5,000 years, within a socioeconomic perspective. We postulate that shark teeth in mortuary contexts were complex, entangled objects that were both mnemonics and instruments. All at the same time, shark teeth were (1) an emblem of a real creature with spectacular predatory abilities, (2) an icon of transformational and spiritual power, (3) a symbol of a society’s maritime way of life, and (4) a tool–a conduit through which a person could gain access to supernatural abilities. When shark teeth were exchanged, all of these properties may have been transferred, suggesting that reinforcing relationships between societies conducting the exchange was as important as gaining access to the supernatural powers of the teeth.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.066

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 studies0.0030.006
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.239
Teacher spread0.209 · 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 designQualitative
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

Citations45
Published2012
Admission routes1
Has abstractyes

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