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Record W6982968817

La opinión editorial sobre ciencia y tecnología en Costa Rica: análisis de contenido en el diario La Nación (enero a junio del 2015)

2017· other· es· W6982968817 on OpenAlexaboutno aff

Bibliographic record

VenueInvestigative News in Education (Universidad de Costa Rica) · 2017
Typeother
Languagees
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsWork (physics)Context (archaeology)Quarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

En los procesos de formación de opinión pública, la capacidad de los medios de
\ncomunicación de establecer agenda temática y de incidir en otros líderes de opinión, los
\nconvierte en actores clave en los procesos de comprensión pública de la ciencia y la
\ntecnología.
\nA partir del contenido que se publica en los medios de comunicación, especialmente
\nen prensa digital, se encadena un proceso de difusión que en la actualidad empieza por
\nenlazar ese contenido a los perfiles personales o institucionales en redes sociales como
\nFacebook y Twitter, donde otros interesados los volverán a circular, sin necesidad de
\ningresar al sitio web original, fomentando con ello la visibilidad de temas, legitimando
\nvoceros y fomentado discusión pública.
\nEl estudio que se presenta contiene un análisis de contenido sobre la opinión
\neditorial empresarial publicada sobre ciencia y tecnología del diario La Nación, periódico
\nde mayor cobertura y tradición en Costa Rica. El objetivo fue establecer las características
\nde estas publicaciones en el periodo de enero a junio 2015, con el propósito de comprender
\nla formación de agenda del medio y brindar insumos que permitan estrategias de incidencia
\nen prensa en los procesos nacionales de comunicación pública de la ciencia.

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)0.003
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.374
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.015
Meta-epidemiology (narrow)0.0020.003
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.003
Science and technology studies0.0010.007
Scholarly communication0.0010.002
Open science0.0050.001
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0010.002

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 head0.016
GPT teacher head0.319
Teacher spread0.303 · 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
GenreOther

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
Published2017
Admission routes1
Has abstractyes

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