Bibliographic record
Abstract
On traditional, "unbounded" approaches to rationality and morality, human behavior can look less than rational and rather indifferent to the rules of morality.My aim is to present Gerd Gigerenzer's "bounded" theories of rationality and morality as plausible alternatives to these traditional approaches.In Gigerenzer's view, both rationality and morality are a function of the mind and environment, and this is in contrast to the traditional view according to which they are not bound to the environment and are thus a function of the mind only.The intuition that humans are largely rational and moral is preserved through Gigerenzer's bounded approach; but because on this approach morality is a function of the mind and environment, there is a strong commitment to the idea that moral luck is real.The idea that moral luck is real is not without controversy and, after a discussion of what we are talking about when we talk about moral luck, I respond to two of the most important arguments against the reality of moral luck.By defending the reality of moral luck in this way, I defend the plausibility of the bounded approach that implies it.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.016 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".