From Peripheral to Integral? A Digital-Born Journalism Not for Profit in a Time of Crises
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 article explores the role of peripheral actors in the production and circulation of journalism through the case study of a North American not-for-profit digital-born journalism organization, <em>The Conversation Canada</em>. Much of the research on peripheral actors has examined individual actors, focusing on questions of identity such as who is a journalist as opposed to emergent and complex institutions with multiple interventions in a time of field transition. Our study explores the role of what we term a ‘complex peripheral actor,’ a journalism actor that may operate across individual, organizational, and network levels, and is active across multiple domains of the journalistic process, including production, publication, and dissemination. This lens is relevant to the North American journalism landscape as digitalization has seen increasing interest in and growth of complex and contested peripheral actors, such as Google, Facebook, and Apple News. Results of this case study point to increasing recognition of <em>The Conversation Canada</em> as a legitimate journalism actor indicated by growing demand for its content from legacy journalism organizations experiencing increasing market pressures in Canada, in addition to demand from a growing number of peripheral journalism actors. We argue that complex peripheral actors are benefitting from changes occurring across the media landscape from economic decline to demand for free journalism content, as well as the proliferation of multiple journalisms.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it