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Record W3043618709 · doi:10.7202/1071939ar

“The Old Village”: Yup’ik Precontact Archaeology and Community-Based Research at the Nunalleq Site, Quinhagak, Alaska

2019· article· en· W3043618709 on OpenAlexvenueno aff
Rick Knecht, Warren Jones

Bibliographic record

VenueÉtudes/Inuit/Studies · 2019
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersArts and Humanities Research Council
KeywordsArchaeologyArchaeological recordPermafrostArcticThreatened speciesHistorical archaeologyGeoarchaeologyPrehistoryCultural heritageHistoryGeographyEcologyOceanographyGeology

Abstract

fetched live from OpenAlex

Centred on the underresearched precontact archaeology of southwest coastal Alaska, the Nunalleq project is a decade-long collaboration between the Yup’ik village of Quinhagak and the University of Aberdeen. The Nunalleq archaeological site, like countless others in the Arctic, is being rapidly destroyed by the combined effects of global warming. Newly thawed permafrost soils are extremely vulnerable to rapid marine erosion from rising sea levels and decreases in seasonal ocean ice cover. Organic artifacts at the site have been preserved in remarkably intact condition, revealing an extraordinary record of precontact Yup’ik culture. But with the disappearing permafrost, this archaeological and ecological record is gradually decomposing, and recovery and analysis has become time critical. The Nunalleq project is a community-based response to locally identified needs to both recover threatened archaeological heritage and to find new ways to reconnect young people to Yup’ik culture and tradition. The results of the project have far exceeded our original expectations. Similar collaborative efforts may be the best hope for addressing threatened archaeological heritage in the North and beyond.

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 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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0240.002
Scholarly communication0.0000.000
Open science0.0010.004
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.002

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 head0.175
GPT teacher head0.450
Teacher spread0.275 · 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 teacher head, not a consensus.

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

Citations23
Published2019
Admission routes1
Has abstractyes

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