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Record W2899276015 · doi:10.21900/j.median.v14i1.62

Cosmopolitical technologies and the demarcation of screen space at Cine Kurumin

2018· article· en· W2899276015 on OpenAlexaff
Sarah Shamash

Bibliographic record

VenueMedia-N · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVisionThe ImaginaryPoliticsSimulacrumIndigenousSociologyMedia studiesAestheticsSpace (punctuation)Representation (politics)HegemonyVisual artsArtPolitical scienceAnthropologyLawPhilosophy

Abstract

fetched live from OpenAlex

“Our fight today is to demarcate our space on the screen, when we can no longer demarcate our lands.” I cite Ailton Krenak, one of Brazil’s most influential Indigenous leaders, at his keynote address at the opening of the Cine Kurumin film festival in Salvador, Brazil, to engage with cinematic languages on the margins of dominant media. I experience the festival as an active immersion into imaginaries that forward the process of “decoloniality” (Mignolo). As Sueli Maxakali articulated during a roundtable of Indigenous women filmmakers, the Shaman must dream in order to choose the name of the films made in her community. The production processes of these films were conceived outside the structures of any capitalist market economy; rather, the festival offered an alternate space to take a deliberate leap into expressive audio and oral visual experiences, cultures, languages, politics, and imaginaries resisting ongoing violence entrenched in capital and coloniality. Through a discussion of the festival curation, roundtable discussion, and through a film analysis, I elaborate how the sacred, spiritual, and social are constituent elements of cosmopolitical visions. I argue that film and video as cosmopolitical technologies are unsettling established conceptions of nature and culture, of politics and representation both on and off-screen. Witnessing the Cine Kurumin festival – the totality of the experience becomes an immersive and transformative space for decolonizing the imaginary while disturbing hegemonic political, conceptual, and representational agendas.

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0040.012
Scholarly communication0.0080.005
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.025
GPT teacher head0.223
Teacher spread0.198 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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