THE CONVERSATION, TEN YEARS ON: ASSESSING THE IMPACT OF A UNIQUE SCHOLARLY PUBLISHING INITIATIVE
Bibliographic record
Abstract
The Conversation (theconversation.com) represents a unique model for communicating scholarly research to the general public via explanatory journalism. Rather than relying on scholars’ personal networks, the promotional efforts of university press offices, or requests from science journalists for comments on current developments, The Conversation offers a platform for scholars across all disciplines to pitch their own stories, gain support from its in-house journalistic staff to develop those stories for a general audience, and see the resulting articles published under Creative Commons licences, enabling them to be republished by commercial and public service news outlets around the world. The overall success of this model, which may be described as ‘journalism-as-a-service’, is evident: articles from The Conversation are regularly republished by major international news outlets from the New York Times through CNN to The Guardian, as well as by domestic outlets across the eight countries and regions in which The Conversation now operates. This panel provides a broad-ranging and multi-faceted assessment of the status of the Conversation project, in its tenth year of operation. The current COVID-19 crisis has particularly highlighted the crisis of expertise and unevenness of scientific literacy amongst journalists, politicians, and the general public. The panel’s assessment of the successes and failures of one of the leading digital science communication initiatives of the past decade provides an important reality check, and offers new insights on what can be done to increase the visibility and impact of rigorous scholarly perspectives from all disciplines of research in public and political debates.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".