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Record W4393019798 · doi:10.7202/1106906ar

“You Help Us Tell our Story”: Making Inuvialuit Living Histories in Digital and Real Time

2023· article· en· W4393019798 on OpenAlexaffvenue
Ethel-Jean Gruben, Ashley Piskor, Mervin Joe, Lena Kotokak, Natasha Lyons, Lisa Hodgetts, Kate Hennessy, Elizabeth A. Edgerton, David W. Stewart, Charles Arnold, Chris von Szombathyix, Jasmine Lukuku

Bibliographic record

VenueÉtudes/Inuit/Studies · 2023
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of CalgarySimon Fraser UniversityWestern UniversityNunavut Research Institute
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Inuvialuit have always created culture through our/their living and land-based practices. For us, making culture means doing, practicing, and sharing activities and songs and country food, on the land and in town, together with our families and communities. These layers of history are embedded in the landscape of Inuvialuit Nunangat, our homeland, and in the voices of Elders past and present speaking about their knowledges and experiences. In this paper, we describe how Inuvialuit communities are practicing our living traditions today and capturing them using digital methods to produce a new Inuvialuit Living History website that celebrates the past, present, and future of our communities.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, 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 score0.432
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.072
GPT teacher head0.393
Teacher spread0.321 · 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

Citations2
Published2023
Admission routes2
Has abstractyes

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