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Encantos e decepções do rádio público estatal

2020· article· pt· W4407911731 on OpenAlexaff
Sergio Ricardo Quiroga

Bibliographic record

VenueRadiofonias – Revista de Estudos em Mídia Sonora · 2020
Typearticle
Languagept
FieldSocial Sciences
TopicRadio, Podcasts, and Digital Media
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsPolitical scienceHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

Este artigo procura examinar a constituição, programação, audiências e diálogo social de duas estações de rádios estaduais na província de San Luis: Radio Universidad em Villa Mercedes (San Luis, Argentina) - FM 97.9 e Radio Municipalidad de la Punta 87.7 em La Punta (San Luis, Argentina). As duas rádios públicas buscam se diferenciar das rádios comerciais com uma grade que possui conteúdo adequado à sua percepção do público. Ambas se esforçam para ter uma programação alternativa, não tradicional em sua forma e estética, uma vez que a chamada mídia pública deve ter uma grande variedade de vozes e nuances e ter uma diversidade de opiniões trabalhando com conteúdos destinados a um público heterogêneo. Rádio universitária em Villa Mercedes (San Luis, Argentina) - A FM 97.9 foi criada em junho de 2015 e a Rádio Municipalidad de la Punta 87.7 em 19 de outubro de 2016. Ambas as estações são financiadas por recursos públicos, no primeiro caso por duas faculdades (FCJES) e (FICA) da Universidade Nacional de San Luis, na cidade de Villa Mercedes, e a segunda por um orçamento do município de La Punta (SL).

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)0.004
metaresearch head score (Gemma)0.010
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 score0.036
Threshold uncertainty score0.107

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0060.004
Scholarly communication0.0080.005
Open science0.0010.006
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0320.004

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 head0.039
GPT teacher head0.295
Teacher spread0.256 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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