Behind Closed Doors: Publicity, Secrecy, and the Quality of Deliberation
Bibliographic record
Abstract
T HERE are many reasons to keep secrets.Some of these reasons will inevitably be better than others.With regard to public policy in a liberal democracy, all reasons for secrecy deserve some scrutiny and justification.Liberal democracy contains a presumption in favor of publicity although it in no way denies the necessity of secrecy.One of the more intriguing reasons for secrecy invokes it for the sake of publicity.This is what theorists are doing when they defend secrecy on the grounds that it enhances deliberation.When theorists argue that the "glare" of publicity makes it difficult to argue reasonably, they imply that deliberation in secret will result in more publicizable outcomes.1 This appears to contradict a cornerstone of deliberative democratic theory: secrecy is fertile ground for private or non-public reason, while public reason flourishes in the open spaces of a public sphere.In what follows, I outline this contradiction in more detail and offer a typology of public reason to sort out the positive effect of publicity from its harmful effect.I argue that the distinction between public reason and private reason has dominated debate within deliberative democratic theory to such an extent that the harmful effects of publicity have been under-theorized.In order to understand just what goes wrong with deliberation under the glare of publicity, I develop a concept of plebiscitory reason.Private reason fails a democratic accountability test.Plebiscitory reason fails a Socratic accountability test.Private reasons are not general enough to appeal to all those affected while plebiscitory reasons are too poorly argued, shallow or manipulative to serve as acceptable justifications of public policy.The question that should concern theories of deliberative democracy is: how can we mitigate or contain plebiscitory reason in the public sphere?The corollary to this is: how can we contain private reason behind closed doors?With regard to the first question, I argue that a clear
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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 | 0.034 | 0.154 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 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".