Bibliographic record
Abstract
According to Wlodek Rabinowicz's fitting-attitude analysis of comparative value, it is possible to analyse both standard and non-standard value relations in terms of the standard preference relations and two levels of normativity. In a recent article, however, Johan Gustafsson has argued that Rabinowicz's analysis violates a principle of value–preference symmetry, according to which for any value relation, there is a corresponding preference relation. Gustafsson has proposed an alternative analysis which respects this principle and which allegedly accounts for the idea that originally motivated Rabinowicz's analysis, namely, that in some cases different preference relations between a pair of items are equally permissible. The goal of my article is to show that the arguments offered by Gustafsson in favour of his account do not succeed. In particular, I argue that Gustafsson faces a dilemma: either he abandons the principle of value–preference symmetry or he cannot make conceptual room for multiple permissible preferences.
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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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.007 | 0.028 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".