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Record W7068833510

[no title]

2022· other· en· W7068833510 on OpenAlexaboutno aff

Bibliographic record

VenueDirectory of Open access Books (OAPEN Foundation) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsMovie theaterPeriod (music)Context (archaeology)World War IIInstitution
DOInot available

Abstract

fetched live from OpenAlex

The National Film Board of Canada (NFB) was created in 1939 to produce, distribute, and promote Canadian cinema both domestically and abroad. During the early years of the NFB, its creative output was largely informed by the turbulent political and social climate the world was facing. World War II, Communism, unemployment, the role of labour unions, and working conditions were all subjects featured by the NFB during the period from 1939 to 1946. In Filming Politics, author Malek Khouri explores the work of the NFB during this period and argues that the political discourse of the films produced by this institution offered a counter-hegemonic portrayal of working class people and presented them as agents of social change. These films also saw an organic link between Canadian struggles for social progress, in the war against fascism and for peace, and those promoted at the time by the Soviet Union. Khouri also analyzes the various social, institutional, and political elements that contributed to the formation of the NFB's discourse. Filming Politics brings to light a number of films from the early years of the NFB, most of which have long been forgotten. Khouri presents a thorough reading of these films and the historical context within which they were produced and viewed. As such he proposes a radically new outlook on the films from how they have been appropriated in previous studies on Canadian cinema.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Open science, Insufficient 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 score0.651
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0080.011
Open science0.0330.026
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.6630.012

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 head0.116
GPT teacher head0.437
Teacher spread0.321 · 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
Published2022
Admission routes1
Has abstractyes

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