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Record W7094300621

Camara de Combate. Latin American film festival(s) as reflection-action

2020· article· en· W7094300621 on OpenAlexaboutno aff

Bibliographic record

VenueOAR@UM (University of Malta) · 2020
Typearticle
Languageen
FieldComputer Science
TopicTeaching and Learning Programming
Canadian institutionsnot available
Fundersnot available
KeywordsLatin AmericansPoliticsDiasporaMovie theaterDictatorshipLatin American studies
DOInot available

Abstract

fetched live from OpenAlex

Cámara de Combate is an artwork composed of series of banners inspired by revolutionary cultural movements originated in Latin America, namely, Third Cinema and Latin American conceptualism. I graphically rendered citations onto the robust material of banners, all taken from Third Cinema filmmakers, who first emerged in 1960s in an era of political upheaval in Latin America. They used the camera as a political weapon to engage revolutionary social, cultural, and political ideas in the region and to incite political consciousness and action. I made a direct correlation with Latin America’s contemporary political context as it relates to American, Canadian, and European interventionism and oppressive regimes, with Latin American Film Festivals situated outside of Latin America. Cámara de Combate, was exhibited in the patio of Vancouver’s Cinematheque as part of the seventeenth edition of the Vancouver Latin American Film Festival in 2019. Some of the questions explored within this artistic inquiry are, what is the role of artists living in the diaspora vis-à-vis Latin American political consciousness? What is the role of Latin American film festivals outside of Latin America in relation to audience and community participants? This text offers a reflection on my artwork and its line of investigation within a diaspora film festival space. I explore some of the philosophical and theoretical currents and political contexts that influenced this work and how it was received within the festival space.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.947
Threshold uncertainty score0.492

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.037
GPT teacher head0.257
Teacher spread0.220 · 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 designOther design
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
Published2020
Admission routes1
Has abstractyes

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