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Record W4225391652 · doi:10.1038/s41467-022-29818-z

Indigenous oyster fisheries persisted for millennia and should inform future management

2022· article· en· W4225391652 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of CanadaHakai InstituteTemple UniversityNational Geographic SocietyNational Science Foundation
KeywordsIndigenousOysterStewardship (theology)FisheryFisheries managementContext (archaeology)Historical ecologyGeographyReefMarine protected areaFishingEcologyPolitical scienceBiologyArchaeologyHabitat

Abstract

fetched live from OpenAlex

Historical ecology has revolutionized our understanding of fisheries and cultural landscapes, demonstrating the value of historical data for evaluating the past, present, and future of Earth's ecosystems. Despite several important studies, Indigenous fisheries generally receive less attention from scholars and managers than the 17th-20th century capitalist commercial fisheries that decimated many keystone species, including oysters. We investigate Indigenous oyster harvest through time in North America and Australia, placing these data in the context of sea level histories and historical catch records. Indigenous oyster fisheries were pervasive across space and through time, persisting for 5000-10,000 years or more. Oysters were likely managed and sometimes "farmed," and are woven into broader cultural, ritual, and social traditions. Effective stewardship of oyster reefs and other marine fisheries around the world must center Indigenous histories and include Indigenous community members to co-develop more inclusive, just, and successful strategies for restoration, harvest, and management.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.023
GPT teacher head0.274
Teacher spread0.251 · 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