A MIXED BENTHAM-RAWLS CRITERION FOR INTERGENERATIONAL EQUITY: THEORY AND IMPLICATIONS
Bibliographic record
Abstract
Ranking development programs using integrals of discounted utilities can yield drastic consequences that offend our sense of justice. New alternative social welfare criteria should be considered. A reaction to discounted utilitarianism is to moderate its effects by adding to the social welfare function a second term that takes seriously the welfare of the generations that live in the far distant future. Chichilnisky proposes a social welfare function that has two desirable properties: (i) non-dictatorship of the present, and (ii) non-dictatorship of the future. However, in many economic models, there exists no optimal path under the Chichilnisky criterion. We introduce a third desideratum: "non-dictatorship of the least advantaged, " and propose a new welfare criterion that is morally compelling. It is a weighted average of two terms: (a) the sum of discounted utilities, and (b) the utility level of the least advantaged generation. We derive necessary conditions to characterize growth paths that satisfy our criterion, and show that in some models with familiar dynamic specifications, an optimal path exists and displays appealing characteristics.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 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".