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Record W2177531041 · doi:10.48336/82ky-xc52

Fishermen's foodways on the Petit Nord: faunal analysis of a seasonal fishing station at the Dos de Cheval site (EfAx-09), Newfoundland

2025· dissertation· en· W2177531041 on OpenAlexaffabout
Stéphane Noël

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2025
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFoodwaysFishingSubsistence agricultureZooarchaeologyGeographyArchaeologyFisheryCommercial fishingConsumption (sociology)EcologyArtBiologyAgriculture

Abstract

fetched live from OpenAlex

Archaeological excavations at the migratory French cod fishing station site of Dos de Cheval (EfAx-09), provided a substantial collection of faunal remains which can be used to study fishermen foodways. Migratory fishing voyages presented some material constraints on the type of food that could be transported and conserved. While archival documents such as provisioning contracts and travel accounts suggest the kind of food products that were brought on board, they only vaguely discuss the incorporation of wild meat in the fishermen's diet while they were on shore. Using zooarchaeological, archaeological and historical data, the present thesis explores specific aspects of food provisioning, but also identity and social status differentiation in food consumption among the Petit Nord fishermen. It is argued that hunting was mainly a privilege of the officers, although ordinary fishermen exploited a variety of seabirds and shorebirds. The subsistence at Dos de Cheval was based almost entirely on domestic mammals, wild land mammals being used only occasionally.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.377
Threshold uncertainty score0.758

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.043
GPT teacher head0.334
Teacher spread0.291 · 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

Citations7
Published2025
Admission routes2
Has abstractyes

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