The minipublic bubble: how the contributions of minipublics are conceived in Belgium (2001–2021)
Bibliographic record
Abstract
Abstract Deliberative minipublics—participatory processes combining civic lottery with structured deliberation—are increasingly presented as a solution to address a series of problems. Whereas political theory has been prolific in conceiving their contributions, it remains unclear how the people organizing minipublics in practice view their purposes, and how these conceptions align with the theory. This paper conducts a thematic analysis of the reports of all the minipublics convened in Belgium between 2001 and 2021 (n= 51) to map whether and how justifications coincide with the theory. The analysis reveals an important gap: minipublics are in practice predominantly presented as contributions to policymaking, while more deliberative functions remain peripheral. Some common practical purposes also remain under-theorized, in particular their capacity to bridge the gap between citizens and politics. This desynchronization, combined with a plethora of desired outcomes associated with minipublics, indicates the creation of a minipublic bubble which inflates their capacity to solve problems.
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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 | 0.013 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.005 |
| 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".