MétaCan
Menu
Back to cohort
Record W4242940457 · doi:10.24908/iqurcp.8895

Arviq! The Northern Hunter’s Spiritual Connection to Animals and Community Presenter:

2018· article· en· W4242940457 on OpenAlexvenueaboutno aff
Chelsea Drent

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsArgument (complex analysis)SociologyValue (mathematics)MythologyEnvironmental ethicsAnthropologyHistoryPhilosophyClassics

Abstract

fetched live from OpenAlex

In Inuktituk, nuna means the land. It means the rocks, rivers, mountains and the forests. Nuna is everything, and all parts of the nuna have an inua, which means a living soul. There is a special, if not sacred relationship between members of northern communities and the nuna. However, these sacred relationships are all too often glossed over, if not forgotten. In the social sciences, author John Sorenson articulates a critical argument and evocative opinions about hunting in his article; Hunting is a Part of Human Nature (John Sorenson, “Hunting is a Part of Human Nature,” Culture of Prejudice, Arguments in Critical Social Science. Eds. Judith Blackwell, Murray Smith, John Sorenson, (Canada: Broadview Press, 2003).Sorenson demonstrates that hunting is an unnatural human activity which is linked to a cultural domination over animals. However, in these statements Sorenson neglects to consider the northern hunter in Inuit communities around the world. Cultural myths, social constructions and daily activities prove that hunting animals is a core value to how many Inuit peoples relate to each other and perceive themselves in the cosmos. This is a study that examines the relationship of people, land, animals and faith in order to understand the significance of hunting within Inuit cultures.

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)0.001
metaresearch head score (Gemma)0.002
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.959
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0100.003
Scholarly communication0.0030.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0540.012

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 head0.212
GPT teacher head0.468
Teacher spread0.255 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueInquiry Queen s Undergraduate Research Conference ProceedingsSame topicIndigenous Studies and EcologyFrench-language works237,207