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Record W7012912341

The Fast Runner

2010· article· en· W7012912341 on OpenAlexaboutno aff

Bibliographic record

VenueInsecta mundi · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousStorytellingFeature filmLegendEPICMovie theaterFilmmakingFront (military)Video production
DOInot available

Abstract

fetched live from OpenAlex

One of the most important Native films of all time, Atanarjuat, the Fast Runner tells a powerful and moving story about honor, betrayal, vengeance, and redemption. Set in the vast, visually stunning Arctic landscape, it was the first feature film written, directed, and acted entirely in Inuktitut, the language of Canada’s Inuit people. Canada’s top-grossing release of 2002, the film became an international phenomenon, receiving the prestigious Camera d’Or Award at the Cannes Film Festival and earning rave reviews from every quarter, including Margaret Atwood (“like Homer with a video camera”), Claude Lévi-Strauss, Jacques Chirac, and Roger Ebert. “The Fast Runner”: Filming the Legend of Atanarjuat takes readers behind the cameras, introducing them to the culture, history, traditions, and people that made this movie extraordinary. Michael Robert Evans explores how the epic film, perhaps the most significant text ever produced by indigenous filmmakers, artfully married the latest in video technology with the traditional storytelling of the Inuit. Tracing Atanarjuat from inception through production to reception, Evans shows how the filmmakers managed this complex intercultural “marriage”; how Igloolik Isuma Productions, the world’s premier indigenous film company, works; and how Inuit history and culture affected the film’s production, release, and worldwide response. His book is a unique, enlightening introduction and analysis of a film that serves as a model of autonomous media production for the more than 350 million indigenous people around the world.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.209
Teacher spread0.190 · 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 designNot applicable
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
Published2010
Admission routes1
Has abstractyes

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