Media Coverage of Scientific Meetings
Bibliographic record
Abstract
CONTEXT: Although they are preliminary and have undergone only limited peer review, research abstracts at scientific meetings may receive prominent attention in the news media. We sought to describe news coverage of abstracts, characterize the research, and determine subsequent full publication in the medical literature. METHODS: We searched Lexis-Nexis to identify news stories printed in the 2 months following 5 scientific meetings held in 1998 (12th World AIDS Conference, American Heart Association, Society for Neuroscience, American Society of Clinical Oncology, and the Radiological Society of North America). We searched MEDLINE and contacted authors to determine subsequent publication in the medical literature within 3-3.5 years of the meetings. RESULTS: A total of 252 news stories reported on 147 research abstracts (average, 50 per meeting); 16% of the covered abstracts were nonhuman studies, 24% randomized trials, and 59% observational studies. Twenty-one percent of the human studies were small (ie, involving <30 subjects). In the 3 years after the meetings, 50% of the abstracts were published in high-impact journals (based on Institute for Scientific Information ratings), 25% in low-impact journals, and 25% remained unpublished. The publication record of the 39 abstracts receiving front-page newspaper coverage was almost identical to the overall rate. Meeting organizers issued press releases for 43 abstracts; these were somewhat more likely to receive prominent news coverage (35% covered on front page vs 23%, P =.14), but were no more likely to be published. CONCLUSIONS: Abstracts at scientific meetings receive substantial attention in the high-profile media. A substantial number of the studies remain unpublished, precluding evaluation in the scientific community.
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 | 0.078 | 0.072 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.061 | 0.012 |
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; both teacher heads agree on what is shown here.
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".