Bibliographic record
Abstract
This paper explores the compelling hedonistic intuition that emotions affect happiness because they are states of pleasure and displeasure . The discussion focusses on two constraints on a plausible version of hedonism and explains which accounts of the emotions satisfy these constraints. Section 1 revolves around the nonalienation constraint : the constituents of a subject’s happiness must engage him or her. We argue that the intuition that emotions have prudential value presupposes that emotions are forms of engagement, a condition that only some accounts of the emotions satisfy. Section 2 centres around the unity constraint : if we acknowledge a great variety of (dis)pleasures, we still need to understand what makes all of them (dis)pleasures. Conceiving of the emotions as forms of engagement, we contend, allows us to resolve the difficulties concerning the variety and unity of (dis)pleasures that weigh on traditional hedonism. In section 3, we defend the form of affective hedonism that has emerged. We argue that the approach can be extended from emotions to other affective states and that the central role we give to action tendencies in our conception of affectivity does not call into question the idea that emotions contribute to happiness because of their hedonic value.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".