Replication Data and Code for: The Slave Trade and the Origins of Matrilineal Kinship
Bibliographic record
Abstract
Matrilineal kinship systems -- where descent is traced through mothers only -- are present all over the world but are most concentrated in sub-Saharan Africa. We explore the relationship between exposure to Africa's external slave trades, during which millions of people were shipped from the continent during a 400-year period and the evolution of matrilineal kinship. Scholars have hypothesized that matrilineal kinship, which is well-suited to incorporating new members, maintaining lineage continuity, and insulating children from the removal of parents (particularly fathers), was an adaptive response to the slave trades. Motivated by this, we test for a connection between the slave trades and matrilineal kinship by combining historical data on an ethnic group's exposure to the slave trades and the presence of matrilineal kinship following the end of the trades. We find that the slave trades are positively associated with the subsequent presence of matrilineal kinship. The result is robust to a variety of measures of exposure to the slave trades, the inclusion of additional covariates, sensitivity analyses that remove outliers, and an IV estimator that uses a group's historical distance from the coast as an instrument. We also find evidence of a complementarity between polygyny and matrilineal kinship, which were both social responses to the disruption of the trades.
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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 | 0.005 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.388 | 0.220 |
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".