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Record W2784133599

Hour of the Furnaces: Beyond Spectatorship

2018· article· en· W2784133599 on OpenAlexaff
Magliocco Ms., Ariana Nicole

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicLatin American Literature Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMovie theaterSubversionHollywoodFilm directorIdeologyPoliticsShot (pellet)AestheticsColonialismCitizen journalismArtDocumentary filmPolitical consciousnessMedia studiesHistoryArt historySociologyPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Hour of the Furnaces is one of those films you never forget watching, at least I never did. Coming in at about 4 hours, the documentary demands to be seen and heard. Shot clandestinely between 1966 and 1968 by Fernando Solanas and Octavio Getino, the film is a revolutionary call to action meant to awaken and inspire socio-political revolution. Despite the decades that exist between myself and this film, it felt more relevant than anything I have seen in years. The documentary speaks of the ever-present legacy of colonialism and neo-colonial policies which devastates the poor and elevates the rich, while illuminating the consumerist ideologies which pacify its citizens and render revolution unthinkable. Solanas and Getino do not think revolution should be dismissed, and this film makes that unmistakably clear. Using guerrilla film tactics, the films produces what Solanas and Getino call Third Cinema, an active subversion of Hollywood cinema. This forces active spectatorship and is meant to awaken the political consciousness of the passive Argentinian viewer, creating an uncomfortable viewing experience, as if to mirror the historical and emotional realities of the Argentinian revolution. It is an abrasive, shocking, and extremely informative documentary, one which left me with the unshakable need to write about it.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.864
Threshold uncertainty score0.812

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.304
Teacher spread0.293 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2018
Admission routes1
Has abstractyes

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