Bibliographic record
Abstract
Abstract John Rawls made the enormously influential suggestion that society can be conceived of as a “cooperative venture for mutual advantage,” governed by a “theory of justice,” which is a set of principles that specify an acceptable division of the “benefits and burdens of cooperation.” It follows, however, that if there are no opportunities for mutually advantageous cooperation in a particular domain of social interaction, then these interactions cannot be governed by principles of justice. Certain commentators have argued that this analysis precludes the application of Rawlsian-style contract theory to questions of intergenerational justice, on the grounds that there can be no reciprocity between non-contemporaneous generations, and thus no possibility of intergenerational cooperation. Yet despite having become influential in the literature, this claim is incorrect, being based upon an overly narrow, direct conception of reciprocity. Many systems of cooperation, both in nature and in human society, are based on indirect reciprocity, where the individual from whom a benefit is received need not be the same as the individual to whom a benefit is provided. Once the possibility of indirect reciprocity is taken into account, one can see that there is no obstacle to the development of systems of intergenerational cooperation. The analysis of such systems provides the foundation for a contractual approach to questions of intergenerational justice.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.010 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".