Referee report. For: Making science public: a review of journalists’ use of Open Science research [version 1; peer review: 3 approved]
Bibliographic record
Abstract
Science journalists are uniquely positioned to increase the societal impact of open science by contextualizing and communicating research findings in ways that highlight their relevance and implications for non-specialist audiences. Through engagement with and coverage of open research outputs, journalists can help align the ideals of openness, transparency, and accountability with the wider public sphere and its democratic potential. Yet, it is unclear to what degree journalists use open research outputs in their reporting, what factors motivate or constrain this use, and how the recent surge in openly available research seen during the COVID-19 pandemic has affected the relationship between open science and science journalism. This literature review thus examines journalists’ use of open research outputs, specifically open access publications and preprints. We focus on literature published from 2018 onwards—particularly literature relating to the COVID-19 pandemic—but also include seminal articles outside the search dates. We find that, despite journalists’ potential to act as critical brokers of open access knowledge, their use of open research outputs is hampered by an overreliance on traditional criteria for evaluating scientific quality; concerns about the trustworthiness of open research outputs; and challenges using and verifying the findings. We also find that, while the COVID-19 pandemic encouraged journalists to explore open research outputs such as preprints, the extent to which these explorations will become established journalistic practices remains unclear. Furthermore, we note that current research is overwhelmingly authored and focused on the Global North, and the United States specifically. Finally, given the dearth of research in this area, we conclude with recommendations for future research that attend to issues of equity and diversity, and more explicitly examine the intersections of open science and science journalism.
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 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 | 0.023 | 0.263 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.018 | 0.010 |
| Insufficient payload (model declined to judge) | 0.329 | 0.144 |
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".