Bibliographic record
Abstract
Abstract Justice and Reciprocity examines the place of reciprocity in egalitarianism, focusing on John Rawls’s conception of ‘justice as fairness’. Reciprocity was central to justice as fairness, but Rawls wasn’t fully explicit about the concept or its diverse roles. The book’s main thesis is threefold. First, reciprocity is not simply a fact of human psychology or a duty to return benefits, but a limiting condition on general duties. Second, such conditions are a natural consequence of thinking of equality as a relational value. However, third, we can identify limits on this conditionality, which explain how some duties of justice can be unconditional. The book explores the ramifications of this argument in a series of debates about distributive justice in which Rawls’s theory has played an organizing role: the justice of productive incentives, duties to future generations, unconditional basic income, and global justice. In each domain, thinking about reciprocity as a limiting condition rather than simply a duty helps explain otherwise puzzling aspects of justice as fairness, in some cases making the view more plausible, but in others underlining limits of the view that will be unappealing to egalitarians of a more unilateral bent. The overall aim of the book is to show that reciprocity involves more than returning benefits, and that limiting justice with reciprocity conditions need not make justice implausibly undemanding. In this way, I hope to rehabilitate reciprocity for egalitarianism.
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 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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".