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Record W6983875807

Spear

2015· other· en· W6983875807 on OpenAlexaboutno aff

Bibliographic record

VenueRMIT Research Repository (RMIT University Library) · 2015
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionFilm industryDanceNarrativeIndigenousFeature filmInclusion (mineral)Film festival
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND Established funding, exhibition and distribution models for feature films in Australia have long been unchallenged, with little variance. These conditions risk constraining certain aesthetic choices and possibilities for experimentation. Connolly, as producer, has been dedicated to challenging these stayed models to develop a new, radical cinematic language. He does this by bringing together artists outside of the film industry to produce works that develop a new cinematic approach. CONTRIBUTION SPEAR is a film project conceived by Connelly (producer) that brought director Stephen Page to transpose a live dance performance work onto the screen. Page tells the story of a young Indigenous man teetering between his ancient culture and the contemporary world, achieving a kind of 'hybrid cinema' that challenges conventional narrative film; it is a work that sits outside the Western paradigm of telling stories onscreen. This, in turn, demands an investigation of a new model of production and exhibition. SIGNIFICANCE As well as innovations in artistic screen practices, Connolly enabled opportunities for young voices from diverse creative practices to participate in the film industry. The significance of the project lies in its capacity to broaden the Australian film industry in new directions. Its success is evidenced by its inclusion at the Adelaide Film Festival (2015), Brisbane Asia Pacific Film Festival (2015) and Toronto International Film Festival (2015); winner Asia Pacific Screen Awards (2015). Funded by the ABC, Adelaide Film Festival, Screen Australia.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0030.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.032

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 head0.051
GPT teacher head0.278
Teacher spread0.227 · 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; both teacher heads agree on what is shown here.

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
Published2015
Admission routes1
Has abstractyes

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