Shaping Policy Discourse in the Public Sphere: Evaluating Civil Speech in an Online Consultation
Bibliographic record
Abstract
The ability of the Internet to function as a public sphere, where citizens can come to public agreement and make recommendations that affect government decisions, has recently come under question. The aggressive style of discourse so prevalent in online discussion has been cited as a significant barrier to the deliberative and open discussion necessary for a effective public sphere. This paper focuses on web-based discussion in a online policy consultation called the Canadian Foreign Policy Dialogue, and examines specific discourse features to evaluate whether the moderated online policy discussion was civil, and whether that civility promoted meaningful interaction among citizens, and between citizens and government. The study results revealed that citizen participants in the dialogue were successful at developing, maintaining, and enforcing norms of civil discourse, and that these norms helped to promote understanding, tolerance, and consensus-building. The study also cautions that civil dialogue alone cannot ensure effective communication between governments and citizens.
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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 | 0.127 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| 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".