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Record W4237379506 · doi:10.3138/9781442683686-fm

Frontmatter

2006· book-chapter· en· W4237379506 on OpenAlexafffundabout
Darrell Varga

Bibliographic record

VenueUniversity of Toronto Press eBooks · 2006
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsUniversity of CalgaryResearch CanadaNSCAD University
FundersUniversity of Toronto
KeywordsComputer science

Abstract

fetched live from OpenAlex

As themes in film studies literature, work and the working class have long occupied a peripheral place in the evaluation of Canadian cinema.Such themes have often been set aside for the sake of a unifying narrative that assumes a division between Québécois and English Canada's film production, a social-realist documentary aesthetic, and what might be called a 'younger brother' relationship with the United States.In Working on Screen, contributors examine representations of socioeconomic class across the spectrum of Canadian film.In doing so, they cover a wide range of class-related topics and deal with them as they intersect with history, political activism, globalization, feminism, queer rights, masculinity, regional marginalization, cinematic realism, and Canadian nationalism.Of concern in this collection are the daily lives and struggles of working people and the ways in which the representation of the experience of class in film fosters or marginalizes a progressive engagement with history, politics, and societies around the world.Working on Screen expands the scholarly debates on the concept of national cinema and builds on the rich, formative efforts of Canadian cultural criticism that focused on the need for cultural autonomy.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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 score0.128
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8720.740

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 head0.026
GPT teacher head0.175
Teacher spread0.150 · 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; the direct Gemma label and the distilled Codex classifier 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
Published2006
Admission routes3
Has abstractyes

Explore more

Same venueUniversity of Toronto Press eBooks→Same topicCinema and Media Studies→French-language works237,207→