Health in Bite Sized Pieces - Discovering Lack of Accessibility and Engagement in Lay Summaries
Bibliographic record
Abstract
The purpose of lay summaries is to summarize a research manuscript in a concise, accessible, and engaging manner for any reader to comprehend. This study seeks to analyze the amount of engagement and accessibility in lay summaries as part of medical research manuscripts. In this study, we analyzed a total of 20 lay summaries, including five from Elife, Multiple Sclerosis and Related Disorders Journal, Epilepsy and Behavior Case Reports, and the Journal of Hepatology. One grader marked each individual lay summary using a customized rubric. The lowest average scores for all journals were 1.5 out of 5 in the accessibility and engagement section of the rubric. The average total score between Elife and EBCR and Elife and the Journal of Hepatology were both significant and were 5.1 and 6.7 marks different, respectively. The results from this study indicate that accessibility and engagement of lay summaries are not as adequate as they should be in the field of medicine. An implication of this study is that it will provide awareness and bring these undiscovered issues into the light, so that authors may consider writing lay summaries that meet the need of their audience. A limitation to this study includes the fact that there was a small sample size.
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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 | 0.030 | 0.264 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".