Communitarianism, Oppositional Cultures, and Human Capital Contagion: Theory and Evidence from Formal versus Koranic Education
Bibliographic record
Abstract
We analyze the implications of communitarianism-the tendency of people to organize into separate culturally homogeneous groups-for individual and group inequality in human capital accumulation. We propose a non-cooperative social interactions model where each individual decides how much time to invest in human capital versus ethnic capital, and his utility from investment in either form of capital is increasing in the investment of his ethnic group in that form of capital. We find that, in equilibrium, the demand for human capital is affected positively by individual and group ability, and negatively by group size. Moreover, two groups that are ex ante identical in ability distribution may diverge in human capital accumulation, with divergence only occurring among their low-ability members. The latter always coordinate on the same type of investment, showing a contagion or herding effect. Furthermore, we find that ethnic and group fragmentation increases the demand for human capital. We validate these predictions of the model using household data from a setting where ethnicity and religion are the primary identity cleavages. We document persistent ethnic and religious inequality in educational attainment. Members of ethnic groups that historically converted to Christianity fare better than those whose ancestors converted to Islam. Consistent with theory, there is little difference between the high-ability members of these groups, but low-ability members of historically Muslim groups choose Koranic education as an alternative to formal education. Also, the descendants of ethnic groups that were evenly exposed to both religions outperform those whose ancestors had contact with only one religion, and local ethnic fragmentation increases the demand for formal education.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".