Scientists in the public sphere: Interactions of scientists and journalists in Brazil
Bibliographic record
Abstract
In order to map scientists' views on media channels and explore their experiences interacting with journalists, the authors conducted a survey of about 1,000 Brazilian scientists. Results indicate that scientists have clear and high expectations about how journalists should act in reporting scientific information in the media, but such expectations, in their opinion, do not always seem to be met. Nonetheless, the results show that surveyed scientists rate their relation with the media positively: 67% say that having their research covered by media has a positive impact on their colleagues. One quarter of the respondents expressed that talking to the media can facilitate acquisition of more funds for research. Moreover, 38% of the total respondents believe that writing about an interesting topic for release on media channels can also facilitate research publication in a scientific journal. However, 15% of the respondents outright agree that research reported in the media beforehand can threaten acceptance for publication by a scientific journal. We hope that these results can foster some initiatives for improving awareness of the two cultures, scientists and journalists; increasing the access of journalists to Brazilian scientific endeavors; stimulating scientists to communicate with the public via social networks.
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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 | 0.009 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".