Cash Transfers, Basic Income and Community Building
Bibliographic record
Abstract
The austerity movement in high-income countries of Europe and North America has renewed calls for a guaranteed Basic Income. At the same time, conditional and unconditional cash transfers accompanied by rigorous impact evaluations have been conducted in low- and middle-income countries with the explicit support of the World Bank. Both Basic Income and cash transfer programs are more confidently designed when based on empirical evidence and social theory that explain how and why cash transfers to citizens are effective ways of encouraging investment in human capital through health and education spending. Are conditional cash transfers more effective and/or more efficient than unconditional transfers? Are means-tested transfers effective? This essay draws explicit parallels between Basic Income and unconditional cash transfers, and demonstrates that cash transfers to citizens work in remarkably similar ways in low-, middle- and high-income countries. It addresses the theoretical foundation of cash transfers. Of the four theories discussed, three explicitly acknowledge the interdependence of society and are based, in increasingly complex ways, on ideas of social inclusion. Only if we have an understanding of how cash transfers affect decision-making can we address questions of how best to design cash transfer schemes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".