Bibliographic record
Abstract
This paper addresses the question of when, why, and how duties are appropriately held to be conditional on reciprocity – compliance on the part of others – focusing on the duties associated with the principle of public reason. There are three main ways to conceive of public reason: as unilaterally binding moral principle, as a moral principle that requires assurance of compliance on the part of others, or as social norm compliance with which provides assurance about other duties that are conditional on reciprocity. The paper maintains that public reason in the fundamental sense cannot be a norm intended to stabilize commitment to justice, but is instead a moral principle, albeit one that is conditional on reciprocity because grounded in the idea of mutual respect despite ongoing moral disagreement. It need not follow, however, that public reason is binding only if some minimum proportion of citizens accept the principle, for we can build reciprocity into the principle by stipulating that unanimous acceptability is required only with respect to points of view accepting the principle. If compliance with law is assured at the requisite level (in part through enforcement), then the duties of public reason associated with authorship of law should only be considered conditional on reciprocity in this 'internal' sense, which is not proportional but bi-lateral.
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 | 0.024 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.031 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".