19 The World Distribution of Household Wealth
Bibliographic record
Abstract
Abstract There has been much recent research on the world distribution of income, but also growing recognition of the importance of other contributions to well‐being, including those of household wealth. Wealth is important in providing security and opportunity, particularly in poorer countries that lack full social safety nets and adequate facilities for borrowing and lending. This chapter finds, however, that it is precisely in the latter countries that household wealth is the lowest, both in absolute and relative terms. Globally, wealth is more concentrated than income, on both an individual and a national basis. Roughly 30 per cent of world wealth is found in each of North America, Europe, and the rich Asian‐Pacific countries. These areas account for virtually all world's top 1% of wealth holders. On an official exchange‐rate basis, India accounts for about a quarter of the adults in the bottom three global wealth deciles, while China provides about a third of those in the fourth to eighth deciles. If current growth trends continue, India, China, and the transition countries will move up in the global distribution, and the lower deciles will be increasingly dominated by countries in Africa, Latin American, and poor parts of the Asian‐Pacific region. Thus wealth may continue to be lowest in areas where it is needed the most.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.032 | 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".