Mobilizing mini-publics: The causal impact of deliberation on civic engagement using panel data
Bibliographic record
Abstract
Deliberative exercises may reinvigorate civic life by building citizens’ capacity to engage in other types of civic activities. This study examines members of a citizens’ panel ( n = 56) who participated in a 6-day deliberative event on climate change and energy transition in Edmonton, Alberta (Canada), in 2012. We compared panellists’ civic engagement, political interest, and political knowledge with those of the general population using a concurrent random digit dialling survey conducted 2.5 years after the event ( n = 405). Panellists are more likely to talk about politics, and volunteer in the community compared to their counterparts in the larger population. Examining three points in time, we reveal a trajectory of increasing political knowledge and civic engagement. Finally, we examine the mechanisms that mobilize panellists into greater civic engagement. This study illustrates how deliberative events could strengthen engagement in civic and political life, depending on the degree to which deliberation was perceived to have occurred.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".