Sharing Science Made Simple: Exploring the Quality and Readability of Published Lay Summaries
Bibliographic record
Abstract
Lay summaries exist to bridge the gap that separates the scientific community from the general public. To foster improved science communication, this study examined the overall quality and readability of published lay summaries across peer-reviewed journals. We obtained 200 lay summaries published in four science journals: eLife, PLOS Medicine, Proceedings of the National Academy of Science (PNAS), and the Journal of Hepatology. Over 900 students across three semesters participated as raters of each summary using a rubric developed to assess the overall quality, accuracy, and accessibility of lay summaries across these journals. The Flesch Reading Ease formula was used to determine the readability of the highest and lowest scoring summaries from each journal. eLife and the Journal of Hepatology had the highest and lowest mean scores for overall quality of 15.6 and 11.7 out of 20, respectively. There were statistically significant differences in accuracy and accessibility found across all journals (p<0.0001). eLife had the highest scoring lay summary for readability. The differences in and lack of consistent scoring across journals with the rubric indicate that deficits exist in the overall quality and readability of published lay summaries. These findings may support the development of guidelines that incorporate elements of the rubric used to write effective lay summaries.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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 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".