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Record W4387447442 · doi:10.18309/ranpoll.v53i3.1839

Loss of vision without insight – the globalized city in Ensaio sobre a Cegueira/Blindness (2008) by Fernando Meirelles

2023· article· en· W4387447442 on OpenAlexaboutno aff
Carolin Overhoff Ferreira

Bibliographic record

VenueRevista da Anpoll · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicCultural, Media, and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBlindnessSightNothingCivilizationMetaphorWonderHomogeneousSociologyAestheticsPsychologyHistoryOptometryPolitical scienceArtSocial psychologyPhilosophyEpistemologyLawMedicineLinguistics

Abstract

fetched live from OpenAlex

Blindness (2008) by Fernando Meirelles used its mode of production as a motive to situate its story in urban spaces that results in fact from an assembled city. Filming Blindness took place in Toronto, São Paulo, Osaka and Montevideo. The resulting assembled globalized city blurs the insight in Saramago into the limits of individuality by offering a homogeneous worldview that levels socio-economic differences, especially between the north and the south. Losing (clear) sight is in the original text in fact a metaphor for the inability of coping with society’s inhumanity in these particular sites. The aim of this article is to study the film by using the concepts of e-motion and indisciplinarity to reveal that Blindness is nothing more than a conventional approach towards a more complex idea on the loss of sight. By marketing it for a globalized audience, the mimics blindness and thus elimenates Saramago’s lucidity regarding the loss of sight of an entire civilization.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.025
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.013
Scholarly communication0.0050.004
Open science0.0000.004
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0020.000

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 head0.273
Teacher spread0.236 · 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 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
Published2023
Admission routes1
Has abstractyes

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