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Record W1147723588 · doi:10.71781/9329

La communauté à l’épreuve de la technologie : les groupes et centres autogérés de cinéastes au Québec et en Ontario à l’heure de la digitalisation

2014· dissertation· fr· W1147723588 on OpenAlexaboutno aff
Clément Lafite

Bibliographic record

VenueOpen MIND · 2014
Typedissertation
Languagefr
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Ce mémoire propose d’étudier les conditions et les perspectives des regroupements d’artistes autogérés face aux changements provoqués par la digitalisation des facteurs de production et de diffusion. L’analyse portée sur l’évolution de ces structures est illustrée par quatre cas spécifiques : le Vidéographe et la Coop Vidéo à Montréal et le Liaison of Independent Filmmakers of Toronto et V-Tape à Toronto. D’un historique de ces organismes, au contexte social et à la pratique artistique liés à leur émergence dans les années 70, cette étude tente de mettre en lumière les transformations de ces structures par l’apparition du médium numérique et d’Internet au tournant du siècle. La recherche s’appuie ici sur une étude approfondie des archives de ces groupes, d’entretiens avec les principaux acteurs concernés et des rapports gouvernementaux permettant de faire ressortir les problématiques actuelles de ces structures autogérées et d’amorcer des réflexions autour de leur pérennité.

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)0.003
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 score0.052
Threshold uncertainty score0.379

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0130.012
Scholarly communication0.0080.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.000

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 head0.062
GPT teacher head0.349
Teacher spread0.287 · 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
Published2014
Admission routes1
Has abstractyes

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