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Extracting Inuit: The of the North Controversy and the White Possessive

2016· article· en· W2611877468 on OpenAlexafffundabout
Bruno Cornellier

Bibliographic record

VenueAmerican Indian Culture and Research Journal · 2016
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of Winnipeg
FundersUniversité de Montréal
KeywordsPossessiveColonialismIndigenousDemocracyWhite (mutation)SociologyHybridityConversationAestheticsWishMedia studiesLawAnthropologyPolitical scienceLinguisticsArtPhilosophyPolitics

Abstract

fetched live from OpenAlex

This article critically explores the heated controversy surrounding screenings of Québécois filmmaker Dominic Gagnon's found-footage documentary of the North 2015, into which he inserted “found” clips of northern Inuit life he had extracted from YouTube as aesthetic capital for southern cinephile jouissance. In conversation with Aileen Moreton-Robinson's theorization of the white possessive, I propose that the vocabulary employed by many of the settler cultural institutions and critics defending the film—e.g., the democratic imperative to protect artistic freedom and allow reasoned dialogue about “difficult” texts to flourish in public spaces—is inextricable from the type of entitlements sustaining settler colonial claims to indigenous lands, and to indigeneity itself, as part of a free and boundless Lockean common. I argue that such default recourse to the democratic imperative of restorative dialogue actually fails to do what it pretends it is meant to do: via mutual understanding and recognition, to solve or resolve the systemic colonial inequalities that Inuit opponents of the film wish to make visible. This common recourse to the “bestowing” of a deliberative public space in the name of a necessary intercultural dialogue reflects the very structure of feeling of liberal colonial settlement and thus reveals a certain cinephilia's subjective and material investment in the white possessive.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0100.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.409
Teacher spread0.378 · 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

Citations3
Published2016
Admission routes3
Has abstractyes

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