Accepting the Digital Challenge: Business Models and Audience Participation in Online Native Media
Bibliographic record
Abstract
Since the mid-1990s, many journalistic initiatives have entered the online environment, either as a continuation of brands already consolidated in conventional formats or as native projects of the new medium. In Spain, the online media scene has just completed its first quarter century of life. This said, the aim of this proposal is to present the evolution of the digital native media in Spain in order to compare their current situation with European success stories. For that purpose, we have conducted a comparative case study between three highlighted Spanish digital native news outlets and three from other European countries. The results show a progressive shift towards a member-funded model, while news outlets try to reduce their dependence on advertising. However, the three European natives seem to be more advanced compared to the Spanish cases as these remain still dependent on advertising revenues to stand upright. Furthermore, two models of participation stand out: the user community and, in particular, the model of collaboration networks. Nevertheless, the study reveals how the analyzed European news outlets are changing the role of the reader through innovative forms of participatory interactivity.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.021 | 0.012 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".