Welfare, ethnicity and altruism : new findings and evolutionary theory
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: The symposium target paper in broader context Part 1: Does Ethnic Heterogeneity Depress Public Altruism in Multi-Ethnic Societies? 1. Urban Begging and Ethnic Nepotism in Russia: An ethnological pilot study 2. Ethnic Diversity, Population Size and Charitable Giving at the Local Level in the United States 3. Ethnic Heterogeneity and Public Spending: Testing the evolutionary theory of ethnicity with cross-national data 4. An Exploratory Comparative Study of the Relationship between Ethnic Heterogeneity and Welfare Politics 5. Reconciling the Differences between Sanderson's and Vanhanen's Results Part 2: Welfare Broadly Defined 6. Ethnic Heterogeneity and Economic Growth: Ethnolinguistic diversity, government and growth 7. Ethnic Diversity, Foreign Aid, Economic Growth, Population Policy, Welfare, Inequality, Conflict and the Costs of Globalism: A perspective on W. Masters and M. McMillan's findings Part 3: Explanation and Prediction: Does evolutionary theory help? 8. The Limits of Chimpanzee Charity: Strategies of meat sharing in communities of wild apes 9. Selfish Cooperation, Loyalty Structures and Proto-Ethnocentrism in Intergroup Agonistic Behaviour 10. Canadian Welfare Policy and Ethnopolitics: Toward an evolutionary model 11. Why Welfare States Rise and Fall: Ethnicity, belief systems, and environmental influences on the support for public goods Part 4: Ethical and Policy Implications 12. Ethnicity, the Problem of Differential Altruism, and International Multiculturalism 13. Affirmative Action and Ethnic Nepotism 14. The Evolutionary Deficit in Mainstream Political Theory
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it