The colonial origins of ethnic warfare: Re-examining the impact of communalizing colonial policies in the British and French Empires
Bibliographic record
Abstract
Communalizing colonial policies (CCPs) include a variety of practices that recognize and institutionalize communal difference among colonized populations, and several qualitative analyses find that they promoted postcolonial ethnic conflict. In contrast, the few quantitative analyses that explore this issue focus on several mechanisms, make conflicting claims, and provide mixed results, thereby suggesting that CCPs do not have general effects. Yet the quantitative findings might be inaccurate for several reasons: Some use the identity of the colonizer as a proxy for CCPs, others measure a CCP but have small samples with limited variation in the focal independent variable, and all of these analyses are unable to explore whether CCPs affect ethnic conflict through different and competing mechanisms. To address these limitations, we create four ideal types of CCPs, gather data on a CCP that conforms to each ideal type, and test the relationships between CCPs and ethnic civil warfare onset using the set of former British and French colonies. We find that a discriminatory CCP is associated with high odds of ethnic civil war onset, especially shortly after independence. Alternatively, differentiating and accommodating CCPs lack general relationships with ethnic civil war onset, and an empowering CCP is negatively related to ethnic warfare in most models.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".