On the Possibility of Measuring Freedom: A Kantian Perspective
Bibliographic record
Abstract
More than three decades after Sen's first formulation of the so-called 'capability approach', practitioners have yet to measure a capability set. This raises fundamental questions about the empirical viability of Sen's approach. In this paper, we argue that Kantian philosophy may offer valuable insights into how to deal with this problem, as the methodological difficulty which has hampered the full operationalisation of the capability approach lies at the heart of Kant's philosophical system. In particular, we will argue that the Kantian notion of autonomy freedom may offer a viable alternative to Sen's notion of opportunity freedom for the operationalisation of an internally coherent normative framework that is compatible with Sen’s representation of human nature. This allows us to propose an operationalisation strategy that focuses (1) on the normative content of choices, and (2) on the process of decision-making, rather than on the measurement of unobservable and counterfactual opportunities.
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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 | 0.020 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.077 |
| Scholarly communication | 0.009 | 0.019 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.008 |
| 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".