¿Qué puede aportar la semiótica triádica al estudio de la comunicación mediática?
Bibliographic record
Abstract
El texto se pregunta por la pertinencia del modelo triádico de significación o semiótica desarrollado por C.S. Peirce para el estudio de la comunicación mediática. El fin es demostrar su aplicabilidad analítica mediante la consideración de algunos estudios mediáticos contemporáneos, y de una breve discusión de un formato televisivo, el reality show, a modo de ilustración. En relación a todos esos casos, se argumenta que el uso del principio no dualista semiótico y la relación lógica de los tres elementos que componen el signo y que explican su acción poseen un poder explicativo y generalizador. Un término tan común pero de dudoso origen científico del punto de vista epistemológico, la audiencia (mediática), adquiere considerable valor heurístico desde la perspectiva semiótica. Otro aporte de la semiótica es superar una dicotomía resistente y poco productiva como la de lo pasivo/activo en el análisis de la relación medios/sociedad.
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.013 | 0.016 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".