How to redistribute? A critical examination of mechanisms to promote global wealth redistribution
Bibliographic record
Abstract
The literature on global redistributive justice deals primarily with the important, yet unresolved issues of why global wealth redistribution may be morally justified or beneficial. However, philosophers and economists who address these issues often do not address the question of how such redistribution should take place. This article seeks to rectify this deficiency and argues that, if a certain level of global wealth distribution is morally justified and, more importantly, beneficial, the question of how it should be promoted is far from trivial. In this context, the analysis opens a new discussion of what form of redistributive measures should be adopted in a multistate reality. The article analyses the potential distributive impact of international tax arrangements. It first explains how international tax arrangements, as an indirect method of redistribution, can promote global distributive objectives. It then assesses whether international tax arrangements offer a more effective global wealth redistribution mechanism when compared to other (indirect) alternatives such as fair trade, international labour, and environmental regulation. The article evaluates the strengths and weaknesses of different redistributive arrangements through the lenses of three criteria: the scope of redistribution, the efficiency of redistribution, and the political feasibility of redistribution. It concludes that, under certain plausible circumstances, international tax redistributive efforts would offer a more effective redistributive option compared to other alternatives.
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 | 0.010 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.033 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".