Television archives, social networks and the young audiences: The example of Internet memes as a way to revitalise public broadcasters’ engagement
Bibliographic record
Abstract
The purpose of this research is to explore the efforts that Spanish public television archives are making to bring their audiovisual content closer to young people via social networks. Specifically, this text focuses on analysing the public television archives of the Spanish national television company RTVE and of the Andalusian regional public television agency (RTVA), known as Archivo RTVE and MemorANDA, respectively. The methodology used is based on both qualitative and quantitative tools, consisting of content analysis and in-depth interviews. The results obtained show that both platforms manage to reach young people, but indirectly through viral videos or Internet memes. The RTVE archive is the most successful among young people because it has a more extensive collection and more resources as well as a policy that is more clearly geared towards the dissemination of its audiovisual heritage. The most negative aspect identified in this study was the repetition of regional clichés, especially in the case of MemorANDA.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".