La actividad periodística y los desafíos de su gestión en los Estados Unidos de América y Europa
Bibliographic record
Abstract
The digital age has opened the doors to numerous opportunities for publishing organizations and journalists, and has increased the number of challenges, particularly those related to the sustainability of the business model. The management of media companies faces a number of profound and disruptive challenges that even significantly defy the logic of various social media industries. This paper aims to understand the sustainability and challenges of media business models and how managers are reacting and adapting their practices in this industry in the field of digital transformation, and in an increasingly competitive market. Thus, the central research questions of this work are: RQ1. What are the main strategies and management practices applied by journalistic companies to achieve the sustainability of their business model and funding? RQ2. To what extent are the revenue streams of digital newspapers growing and how has the funding model of US newspapers differed from that of European ones? This article is based on 6 interviews (out of a total of 90 from a larger study that included executives from media companies based on all continents) with executives from 3 North American (United States and Canada) and 3 European newspaper companies. (Ireland, UK and France).
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".