The Relational Ontology of Amartya Sen’s Capability Approach: Incorporating Social and Individual Causes
Bibliographic record
Abstract
While Sen has written extensively on the social factors of capabilities, the exact nature of these social factors and how they interact to form and influence capabilities is contested and unclear. Consequently, how to coherently integrate social components into capability research remains a concern for those attempting to put the capability approach to practical use. This paper proposes one approach to understanding and integrating the social nature of capabilities. Building upon two recent contributions by Martins, we argue that underpinning Sen’s notion of capabilities is an ontological conception of a relational society. In this perspective, an individual’s capabilities emerge from the combination and interaction of individual‐level capacities and the individual’s relative position vis‐à‐vis social structures that provide reasons and resources for particular behaviors. Crucially, this conception of society is predicated upon a contextual notion of causality that is flexible enough to incorporate both individual and social causes into social analysis.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.022 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".