Bibliographic record
Abstract
Abstract Perfectionism about well‐being is, at a minimum, the view that people's lives go well when, and because, they realize their capacities. It is common to link perfectionism with an idea of human essence or nature, to view well‐being as the unfolding of characteristically human capacities. This article argues that perfectionism would be more plausible if it abandons reliance on the idea of human nature and focuses instead on the unfolding of some valuable capacities that need not be unique to, or shared by all human beings. The article develops this revised perfectionism through the dignitarian approach—the view that we have reason to organize our personal and social life in such a way that we respond appropriately to the valuable features of individuals that give rise to their dignity. According to the resulting proposal—Dignitarian Perfectionism—human individuals' well‐being consists, at least in part, in developing and exercising the capacities at the basis of their dignity. Dignitarian Perfectionism is evaluative all the way down, pragmatic but not unprincipled, and holistic. Furthermore, it can make sense of the role of some generalizations that animated some of the plausibility of traditional perfectionism—and this without the pitfalls of reliance on an idea of human nature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.032 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".