Open journalism: dynamics of change and continuity in news work in the 21st century
Bibliographic record
Abstract
This review of eight years of research into digital media addresses the methodological and epistemological issues and tensions arising out of the emergence of new communicative spaces that have expanded the range of actors involved in the construction of the news. Until recently, journalism has developed as a relatively closed professional culture for the production of knowledge, based on a system of editorial control. Yet digital media technologies have disrupted established concepts of communication, prevailing notions of space and time and the distinction between public and private spheres. The research in this portfolio highlights elements of change and continuity in the way journalists think about and engage in their work, through processes of adaptation shaped by cultural, social, economic and technological factors. The work reveals how far participatory media technologies are transforming how journalists and audiences relate to the news in a profession where norms and routines that have remained, until now, decidedly consistent. But it goes beyond a focus on journalists as a distinct group to advance ideas about how the media environment itself is being reconfigured, particularly due to the development of social media. The research presented here on Twitter reveals how news and information have become woven into social awareness streams that represent a constantly updated public account of the experiences, interests and opinions shared by the platform’s users. They are able to reframe or reinterpret messages through networked platforms that extend the dissemination of news through social interaction, infusing hybridity in news production, selection and dissemination
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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 | 0.020 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.009 | 0.047 |
| Scholarly communication | 0.036 | 0.027 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".