Measuring Lineage: Implications for Family Violence Research in Sub-Saharan Africa
Bibliographic record
Abstract
Previous research on family violence in sub-Saharan Africa highlighted the importance of lineage to women’s experiences of intimate partner violence (IPV). The findings suggest women in patrilineal societies face a greater risk of experiencing IPV than those in matrilineal societies. However, a major critique of this body of work is the operationalization of lineage with ethnicity. This study highlights the weaknesses/strengths of using ethnicity as a proxy for lineage by comparing it to direct measures of lineage. Specifically, we tested the validity of lumping ethnic groups together to create lineage categories against measures that directly ask respondents to self-identify their lineage. We also explored the effects of lineage on different types of IPV. We used representative cross-sectional data collected between May and August 2022 from 1,624 ever-married Ghanaian women aged 18 years and older and residing in three major ecological zones—Coastal, Middle, and Northern Zones—that reflect differences in ecology, culture, and modernity in Ghana. Descriptive and multivariate statistical techniques were used to analyze the data. The findings suggest significant differences in direct (self-identified) and indirect (ethnic) measures of lineage. The majority of respondents who were classified as matrilineal or patrilineal based on their ethnic backgrounds self-reported as belonging to these lineage categories. Both direct and indirect measures of lineage were significantly associated with IPV. However, given the limited operationalization of lineage based on ethnicity, self-identified measures were more useful. While ethnicity remains an important proxy for lineage, self-identified measures of the construct are better if available.
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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 | 0.004 | 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 | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".