Producción y difusión de obras teatrales en las radios generalistas en España (ser, Cope, Onda cero y RNE): cuando el radioteatro es ficción sonora (2014-2024)
Bibliographic record
Abstract
La relación del teatro con otros medios de comunicación ha derivado en diferentes sinergias y formas narrativas alrededor de la idea de lo dramático, aunque siempre contemplándolo como ficción. En este artículo se ha investigado la producción sonora de ficción de las cuatro emisoras radiofónicas generalistas más escuchadas en España según el Estudio General de Medios en 2024 (SER, COPE, Onda Cero y RNE) para poder confeccionar un listado de los textos teatrales adaptados al medio sonoro durante los últimos diez años (2014-2024) que están disponibles a través de sus páginas web o de sus plataformas de audio asociadas. Abstract: The relationship between theatre and the traditionally designated mass media has given rise to various synergies and narrative forms centred on the idea of the dramatic, although always regarded as fiction. This article examines the production of audio fiction by the four most listened-to generalist radio stations in Spain, according to theGeneral Media Study in 2024 (SER, COPE, Onda Cero, and RNE), in order to compile a list of theatrical texts adapted to the audio medium between 2014 and 2024, available on their websites or associated audio platforms.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".