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Record W6910426874 · doi:10.3886/e195623

Replication Data and Code for: The Slave Trade and the Origins of Matrilineal Kinship

2023· dataset· en· W6910426874 on OpenAlexaff

Bibliographic record

VenueICPSR Data Holdings · 2023
Typedataset
Languageen
Field
Topic
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsKinshipPolygynyComplementarity (molecular biology)Ethnic groupLineage (genetic)Range (aeronautics)

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.023
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0090.006
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.180
GPT teacher head0.386
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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Same venueICPSR Data HoldingsFrench-language works237,207