La importancia de las Ciencias de la Comunicación en las campañas sociales
Bibliographic record
Abstract
Las campanas sociales representan la puesta en practica de estrategias de comunicacion en los medios por parte de los poderes publicos y de los organismos sin fines lucro que se preocupan por las causas sociales. Ellas constituyen un elemento poderoso de todo programa educativo que pretende interpelar a los miembros del publico, informarlos y convencerlos de lo positivo de una causa o de un comportamiento saludable. En general, las campanas sociales se realizan inspiradas en las propuestas del marketing social. Segun ciertos investigadores, el exito relativo de las campanas sociales se explica, entre otras cosas, por el hecho que no se explotan bien los conceptos teoricos y metodologicos de las ciencias sociales. Desde nuestro punto de vista, la investigacion en ciencias sociales, y en particular en comunicacion, deberia ser integrada en el proceso del marketing social. En este articulo presentamos los modelos de persuasion mas utilizados en las campanas, algunos modelos teoricos que ayudan a comprender su influencia, asi como ejemplos de como han sido utilizados en algunas campanas, aumentando asi sus posibilidades de exito
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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.
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".