Organizational factors influencing journalists’ use of user-generated content: A case of Canadian radio newsrooms
Bibliographic record
Abstract
Abstract Using an evaluation framework, this study sheds light on the organizational factors that influence the use of user-generated content (UGC) in radio newsrooms. Although communication research is consistently emphasizing rapid changes in technology and the need for journalists to adapt to their multi-platform environments, this study shows that some radio journalists and managers, at least, are still quite conservative in their innovative practices. Through the use of semi-structured interviews with radio managers and journalists in a major Canadian market, five main uses of UGC were identified in the newsroom. These factors were directly related to the perceived notion of the audience and its value to news reporting. Financial pressures, company policy and professional standards are the three main organizational factors that influence these uses and the extent to which the practices were observed. Age, language and sectorial differences did not appear to be influential in this study. These results, however, suggest that work still needs to be done to establish which factors are most relevant in overcoming fears and challenges with respect to innovative UGC use. A better knowledge of the audience could also influence future behaviour.
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 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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".