Bibliographic record
Abstract
In her book Limitarianism, Ingrid Robeyns draws attention to a specific type of moral response to inequality that is often ignored by social and political philosophers, even though it is widely experienced by the public. This is: condemnation of excess. The human capability for justice is based in part on a sense of fairness as proportionality, and the excessive wealth that we may witness both in history and in the contemporary world beggar any reasonable sense of proportionality. Meanwhile, Robeyns shows that excessive wealth also outrages other components of our sense of justice: our care and compassion for the well-being of others; our respect for freedom and aversion to domination; and our revulsion at ill-gotten gains. Three key questions raised by the contributors to this symposium might be highlighted: Where should we draw the ‘riches line’ that marks off excessive wealth? Can Western limitarianism harmonize with Asian philosophies such as Confucianism, which focus on social harmony in which there is enough for all? Why does Robeyns advocate for a cap on wealth as an ideal but not as a point in her practical program for action?
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.013 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".