Bibliographic record
Abstract
What might participatory deliberative democracy look like in complex, mass societies? Cristina Lafont’s Democracy Without Shortcuts (2019) challenges us to revisit this question by taking contemporary democratic theory to task for recommending a variety of shortcuts that would seem to reconcile democratic self-government with complex, mass societies, but do so by requiring ‘blind deference’ of citizens to decisions made by others. Here I make three general points. First, democracy is possible in mass, complex societies just because democratic societies and governments are full of shortcuts, through representation, political, epistemic and advocacy divisions of labour, differentiated institutions, multi-level governance, and trust relationships both among citizens and between citizens and governments. Few of these shortcuts require ‘blind deference’ of citizens. Second, because complex societies are highly differentiated in their structures, they also multiply opportunities for participation in ways that Lafont does not theorise owing to a statist focus on constitutional, rights-based politics. But, third, in arguing against shortcuts, Lafont underscores the importance of assessing the many kinds of principal–agent relationships in complex mass societies to ensure they advance rather than undermine the norms of participatory deliberative democracy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.027 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".