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Record W4393020094 · doi:10.7202/1106902ar

Inughuit Nipaan: The Future of Archaeological Partnerships in Avanersuaq

2023· article· en· W4393020094 on OpenAlexaffvenueabout
Mari Kleist, Matthew Walls, Genoveva Sadorana, Otto Simigaq, Aleqatsiaq Peary

Bibliographic record

VenueÉtudes/Inuit/Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicResearch in Social Sciences
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChemistry

Abstract

fetched live from OpenAlex

Inuit across the Arctic regions have for generations echoed a wish for a greater involvement in research and have voiced the need for direct partnerships that include Indigenous perspectives. As a consequence, researchers are becoming increasingly aware that studying other people’s past and heritage is not an inherent academic right but rather involves developing close Indigenous partnerships. Accordingly, partnership research frameworks are now being recognized as essential foundations to decolonize research practices in the Arctic, as vocalized by Inuit communities. In this paper, Inughuit community members share their personal and shared thoughts and reflections and present how they envision future partnership research approaches, how they can determine the objectives of partnered research, and what archaeology can ultimately contribute in a changing Arctic.

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)0.007
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.120
Threshold uncertainty score0.238

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0190.008
Scholarly communication0.0080.006
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.317
GPT teacher head0.478
Teacher spread0.161 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2023
Admission routes3
Has abstractyes

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