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Record W275230223 · doi:10.1007/s10745-015-9743-3

Kwakwaka’wakw “Clam Gardens”

2015· article· en· W275230223 on OpenAlexafffund
Douglas Deur, Adam Dick, Kim Recalma‐Clutesi, Nancy J. Turner

Bibliographic record

VenueHuman Ecology · 2015
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of VictoriaAssembly of First Nations
FundersSimon Fraser UniversityNational Geographic Society
KeywordsIntertidal zoneProductivityIndigenousNatural (archaeology)GeographyClanFisheryTraditional knowledgeArchaeologyEcologyOceanographyGeologyPolitical scienceLawBiology

Abstract

fetched live from OpenAlex

Abstract The indigenous peoples of the Northwest Coast of North America actively managed natural resources in diverse ways to enhance their productivity and proximity. Among those practices that have escaped the attention of anthropologists until recently is the traditional management of intertidal clam beds, which Northwest Coast peoples have enhanced through techniques such as selective harvests, the removal of shells and other debris, and the mechanical aeration of the soil matrix. In some cases, harvesters also removed stones or even created stone revetments that served to laterally expand sediments suitable for clam production into previously unusable portions of the tidal zone. This article presents the only account of these activities, their motivations, and their outcomes, based on the first-hand knowledge of a traditional practitioner, Kwakwaka’wakw Clan Chief Kwaxistalla Adam Dick, trained in these techniques by elders raised in the nineteenth century when clam “gardening” was still widely practiced.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.988
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.135
GPT teacher head0.433
Teacher spread0.298 · 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

Citations103
Published2015
Admission routes2
Has abstractyes

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