Bibliographic record
Abstract
In this paper I argue that the most fundamental goal of any public policy is to assist the realization of social good. I take it that the idea of social good has developed differently in different political and moral traditions, and focus my analysis on the interplay of liberalism, virtue ethics and the Capability Approach. I argue that the liberal conception of social good, as espoused by its leading exponents, is somewhat problematic, and that it fails to account for meaningful civic associations. Even though liberal thinkers often prioritize an individual’s freedom and autonomy, they do not provide us with concreto principles that can facilitate the realization of these goals. I draw upon the practical functioning of leading liberal democracies, including the United States, Canada and India, emphasizing the role of normative political constraints in policy making. I conclude that the liberal conception of social good stands in an acute need of a fresh principle that can rectify the above anomalies and reinvigorate its moral force, and that such a principle can probably be constructed with the help of Amartya Sen’s Capability Approach and Aristotle’s Virtue Theory.
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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 | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.099 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".