The Metaphysical Case against Luck Egalitarianism
Bibliographic record
Abstract
Luck egalitarianism is the name of a group of theories of justice that subscribe to the idea that a just society compensates for brute luck, but does not compensate for bad outcomes that fall under the responsibility of the agent himself. The theory has gained much popularity over the past decades. Notable defenders of versions of the theory are Dworkin (2000) and Cohen (1989). Centralizing luck in a theory of justice requires a substantial account of luck, and thereby makes the free will debate very important for distributive justice. Luck egalitarianism has been accused of relying heavily on a indeterminist view on free will. However, Richard Arneson (2004) and Carl Knight (2006) have argued that luck egalitarianism is also a plausible view under compatibilist accounts of free will. In this essay I argue that defenders of this view fail to properly distinguish between what T.M. Scanlon (1998) calls attributive and substantive responsibility. Compatibilist accounts of free will and responsibility provide an understanding of the former but not the latter concept, while the latter is the relevant one for justice. Knight and Arneson acknowledge difficulties, but do not deal with them in a satisfactory manner. A rigorous treatment of the argument in the free will debate, has detrimental consequences for the luck egalitarian position. If the libertarian position on free will is wrong, luck egalitarianism collapses into outcome egalitarianism. I argue that, in Dworkin’s terminology, the distinction between brute luck and option luck will turn out arbitrary, or irrelevant, for justice under Scanlon’s distinction. The only plausible version of luck egalitarianism that is different from outcome egalitarianism relies on indeterminism being true.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.065 |
| Scholarly communication | 0.010 | 0.017 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.007 | 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".