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A INDÚSTRIA CULTURAL NO BRASIL: O PODER ECONÔMICO DA MÍDIA TELEVISIVA

2018· article· pt· W4247261619 on OpenAlexaff
Júlio Araújo Carneiro da Cunha

Bibliographic record

VenueAmericanae (AECID Library) · 2018
Typearticle
Languagept
FieldArts and Humanities
TopicCultural, Media, and Literary Studies
Canadian institutionsDalsa Corporation
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

O primeiro grande meio de comunicação em massa foi a impressão, inventada por Johannes Gutemberg no século XV. A tecnologia da impressão possibilitou a difusão de livros e textos para um maior número de pessoas, sendo a Bíblia o primeiro livro impresso por Gutemberg. No período atual, o domínio da comunicação de massa deixou de ser a impressão, e a televisão ocupou seu espaço, atingindo quase toda a população dos países desenvolvidos e em desenvolvimento. Este trabalho tem por objetivo discutir e analisar o fenômeno da mídia televisiva, cujo poder econômico e ideológico reflete diretamente no setor do qual faz parte e na vida cotidiana das pessoas. Para tanto, tratamos da noção de indústria cultural e sua forma de operação, assim como traçamos um breve panorama do setor de emissores de TV no Brasil, e na cidade de São Paulo, com suas características de mercado, como a forte concentração das empresas, apresentando dados que possam subsidiar nossa argumentação. Discutirmos então, de maneira mais pontual, os aspectos econômicos e ideológicos que permeiam a mídia televisiva e como eles estão inter-relacionados, refletindo desafios e dilemas no papel da comunicação de massa.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.003
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0440.006

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 head0.028
GPT teacher head0.246
Teacher spread0.218 · 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
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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