Powers and Faden's Concept of Self-Determination and What It Means to 'Achieve' Well-Being in Their Theory of Social Justice
Bibliographic record
Abstract
Powers and Faden argue that social justice ‘is concerned with securing and maintaining the social conditions necessary for a sufficient level of well-being in all of its essential dimensions for everyone’ (2006: 50). Moreover, social justice is concerned with the ‘achievement of well-being, not the freedom or capability to achieve well-being’ (p. 40). Although Powers and Faden note that an agent alone cannot achieve well-being without the necessary social conditions of life (e.g. equal civil liberties and basic material resources, such as food and shelter), it seems that achievement requires that an agent actually pursue the six dimensions of well-being. In this article, I question the extent to which an individual has an obligation to achieve well-being, even if he or she would choose to do otherwise. For example, can an agent choose to forgo being healthy even if all the social conditions are met in her life, thereby choosing to not achieve well-being? It remains unclear how the dimension of self-determination coheres with the remaining five dimensions of well-being and the extent of society’s obligations toward an individual’s achievement of well-being, even in those instances when society’s actions may go against an individual’s right to self-determination.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.042 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".