Means of Knowledge Dissemination: Are the <i>Café Scientifique</i> and the Artistic Performance Equally Effective?
Bibliographic record
Abstract
An increasing number of health researchers are opting for innovative approaches to communicate research findings. This article compares two methods for disseminating findings to various audiences: the Café scientifique and the artistic performance. Analysis of surveys completed by 78 respondents indicates that the artistic performance is more effective in communicating research findings based on three of the four evaluation criteria used: it generates more questions and emotion among audience members and influences a greater number of individuals to alter their initial understanding of and opinion on an issue. The Café scientifique and the artistic performance both help participants to better understand the topic examined. The arts, however, shine a different light on the issue.
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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 | 0.128 | 0.223 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.017 | 0.017 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".