A Clash Of Cultures: The Integration Of User-Generated Content Within Professional Journalistic Frameworks At British Newspaper Websites
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study examines how national UK newspaper websites are integrating user-generated content (UGC). A survey quantifying the adoption of UGC by mainstream news organisations showed a dramatic increase in the opportunities for contributions from readers. In-depth interviews with senior news executives revealed this expansion is taking place despite residual doubts about the editorial and commercial value of material from the public. The study identified a shift towards the use of moderation due to editors' persistent concerns about reputation, trust, and legal liabilities, indicating that UK newspaper websites are adopting a traditional gate-keeping role towards UGC. The findings suggest a gate-keeping approach may offer a model for the integration of UGC, with professional news organisations providing editorial structures to bring different voices into their news reporting, filtering and aggregating UGC in ways they believe to be useful and valuable to their audience. While this research looked at UGC initiatives in the context of the UK newspaper industry, it has broad relevance as professional journalists tend to share a similar set of norms. The British experience offers valuable lessons for news executives making their first forays into this area and for academics studying the field of participatory journalism. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it