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Record W2601095085 · doi:10.1386/public.27.54.104_7

Tilllutarniit: History, Land and Resilience in Inuit Film and Video

2016· article· en· W2601095085 on OpenAlexaffabout
Heather Igloliorte

Bibliographic record

VenuePublic · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsConcordia University
Fundersnot available
KeywordsVisual artsFilm festivalFeature filmArctic charArtArcticFeature (linguistics)ArchaeologyArt historyGeographyMedia studiesHistoryMovie theaterSociology

Abstract

fetched live from OpenAlex

Abstract In early August 2016, Inuit artists Stephen Agluvak Puskas and Isabella-Rose Weetaluktuk co-curated an original format film festival in Montreal, produced in partnership with Concordia University, the FOFA Gallery and Terres en vues festival. For three evenings in a row, the FOFA Gallery’s outdoor courtyard, which opens onto one of the city’s busiest downtown streets, offered up Inuit ‘country’ food (traditional cuisine like raw seal meat and arctic char), music, Inuit games, and film and video. Each evening featured a series of short and feature films directed by or produced in serious collaboration with Inuit, arranged under three distinct themes; Unikausiit (history), Nuna (land) and Pimmariktuq (resilience). This interview is a conversation between Inuk art historian Heather Igloliorte and Puskas and Weetaluktuk, in which the co-curators reflect on the experience of creating the film festival.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.132
Threshold uncertainty score0.263

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.004
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.001

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 head0.074
GPT teacher head0.210
Teacher spread0.136 · 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 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

Citations0
Published2016
Admission routes2
Has abstractyes

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