Bibliographic record
Abstract
Recently, states and other institutions have undertaken to make restitution for past abuses. Distinctions need to be made between various kinds of restitutive practices that rest on quite different normative grounds. Moreover, the core idea of restitution, in attaching obligation to particular historically grounded relationships, is questionable, and what is being attempted is better explained and justified in terms of a number of standard principles of justice of a non-restitutive kind; for although there is, in principle, a clear case of restitutive justice, its elements rarely, if ever, exist in the real world in an unmixed state. Although there are significant objections to deriving local obligations from principles of universal justice, they have no force in this case. Policies termed ‘restitutive’ may well be justifiable, but they are misdescribed.
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 | 0.038 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.067 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.016 | 0.028 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".