Collective candidacies and mandates in Brazil: Recasting democratic mediation
Bibliographic record
Abstract
Abstract While global discontent with democracy has reached its highest rates since 1995, there is no consensus on what is causing so much democratic backsliding. In Brazil, scholars discussing how to reinvigorate citizens's trust in democratic systems emphasize the need for an understanding of political representation to include issues such as recognition, inclusion, and a thorough assessment of institutional affordances provided by the available instruments for mediation of conflictive political interests. Meanwhile, grassroots activists are exploring the space between civil society and the state to reshape political representation through collective candidacies and mandates. The former refers to organized groups of four or more activists campaigning together for a single seat in government office. The latter involves legislative seats run collaboratively by groups committed to sharing their representative power with their constituents during their term in office. Using abductive reasoning to discuss secondary data and review literature, the paper argues that: (a) growing dissatisfaction with democracy stems from a perceived decline in the ability of its established mechanisms to equitably aggregate and negotiate citizens' diverse interests; (b) power‐sharing, civic imaginaries, trust, mistrust, distrust, and interests are key psychopolitical elements that simultaneously inform citizens' skepticism about democratic institutions and are mobilized to rebuild these mechanisms. Presenting these experiments as products of the Brazilian political system's affordances and highlighting their relevance for creating accountable and inclusive institutions, the paper encourages political psychologists to apply their interdisciplinary tools to study democratic innovations emerging at the intersection of theory and practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".