Bibliographic record
Abstract
In Responding to Global Poverty, Christian Barry and Gerhard Øverland argue that, while exploitation is morally problematic, responsibilities not to exploit are characteristically less stringent than responsibilities not to harm. They even suggest that exploiters’ responsibilities to assist the exploited may be weaker than the responsibilities of culpable bystanders who are able to help the poor but fail to do so We think Barry and Øverland underestimate the prospects of the exploitation argument. In our paper, we suggest that exploitation can plausibly be understood as a kind of harm. If exploitation harms, then it requires special justification and can generate stringent responsibilities not to exploit that have a different ground than those generated by morally culpable failures to assist. This suggests an important way to rehabilitate arguments for poverty relief on the basis of a duty not to harm, and that there is more interesting territory to explore than Barry and Øverland’s arguments suggest.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.050 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.009 | 0.006 |
| 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".