Bibliographic record
Abstract
My investigation of the capabilities approach as a burgeoning theory of global justice underlies the integrated-article format of this thesis, where each chapter treats a discrete but related problem. In Chapter One I survey the rapidly growing philosophical literature on global justice, focusing on contemporary rights-based approaches. I defend capabilities as central to global justice because justice demands that individuals be well positioned to enjoy the prospects of a decent life, measured by how well individuals are actually able to convert resources and opportunities into valuable functionings. In Chapter Two I explore what I take to be the most promising alternative philosophical approach to addressing pressing global challenges in terms of justice: the ethics of care. Just as capabilities help enrich and flesh out the depth and reach rights have, making capabilities a conceptually rich ally of rights, I argue rights signify a powerful ally to an increasingly global ethic of care. In Chapter Three I consider the as yet under examined connection between rights and well-being by exploring Sen’s pioneering work on capabilities. Capabilities provide us with an appropriate measurement for justice to the extent that the rights and well-being of individuals leave them empowered to enjoy a life of dignity that has at least a minimum set of opportunities. In Chapter Four I consider Hugo Grotius’s theory of rights as an important historical basis for developing a capability-based theory of global justice. In Chapter Five I argue that the status and treatment of nonhuman animals is not and cannot be a matter of justice within the structure of John Rawls’s theory, making it inadequate to this extent. I defend capabilities theory as better able to account for why the treatment of nonhuman animals is a matter of justice.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.031 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".