Synthetic biology in the Science Café: what have we learned about public engagement?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Engaging the public on emerging science technologies has often presented challenges. People may hold notions that science is too complicated for them to understand and the venues at which science is discussed are formal and perceived as inaccessible. One approach to address these challenges is through the Science Café, or Café Scientifique. We conducted five Science Cafés across Canada to gauge public awareness of synthetic biology technology, its potential applications, and to evaluate the effectiveness of the Science Café platform as a knowledge-translation tool. Café participants were excited about the potential benefits of synthetic biology technology, but also concerned about the potential risks. And while participants trusted scientists to carry out their research, there was limited confidence that regulators would ensure public safety. Science Cafés as a forum for science to meet society were viewed positively for the relaxed atmosphere, small crowd size and informality of the venue. We conclude that Science Cafés are an effective upstream engagement platform for discussing emerging science technologies.
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.
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 | 0.036 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.001 | 0.011 |
| Open science | 0.003 | 0.000 |
| 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 it