Building Faith in Democracy: Deliberative Events, Political Trust and Efficacy
Bibliographic record
Abstract
Governments have turned to public deliberation as a way to engage citizens in governance with the goal of rebuilding faith in government institutions and authority as well as to provide quality inputs into governance. This article offers a systematic analysis of the literature on the effects of deliberative events on participants’ political efficacy and trust. The systematic review contextualizes the results from a 6-day deliberative event. This case study is distinctive in highlighting the long-term impacts on participants’ political trust and efficacy as key outcomes of the deliberative process unfold, that is, City Council receives then responds to the participants’ recommendations report. Using four-wave panel data spanning 2.5 years and three public opinion polls (control groups), the study demonstrates that participants in deliberative events are more efficacious and trusting prior to and after the deliberative event. Despite the case study’s evidence and the systematic review of existing literature, questions remain about whether enhanced opportunities for citizen engagement in governance can ameliorate low levels of political trust and efficacy observed in Western democracies.
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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 | 0.040 | 0.123 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".