Science Communication and Democracy
Bibliographic record
Abstract
It should first be noted that the topic here is science communication and not scientific discourse. A primary scientific discourse is one produced by a researcher for another researcher. Science textbooks fall into this category, and such discourses are generally geared to specific audiences. Science communication, on the other hand, is not aimed at specialists but at a broader, more disparate, audience. This means that communications about science geared to lay audiences and delivered via various types of media, including the printed press, radio, television and the internet (Jacobi, 1999; Schiele, 2001), are received and interpreted in a cultural, institutional and political environment that is broader than the scientific context of the original discourse (Gregory & Bauer, 2003). They also get caught up in issues of professional communication and the general business of media and networks that generate a very heterogeneous social structure. Our focus here is on science communication in the areas of professional communication and media, apart from the strictly educational and cultural fields. This paper investigates contemporary modes of science communication in society. We wish to show that, contrary to the spirit of the Enlightenment, which fostered the free flow of ideas in the public sphere, making it a condition of democratic debate (Habermas, 1978), science communication is today beset by many and varied at-tempts to control it, and which ultimately threaten the relationship between science, an informed public, and the functioning of democracy.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.028 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".