Gendered Penalties of Divorce on Remarriage in Nigeria: A Qualitative Study
Bibliographic record
Abstract
Seeking the views of metropolitan, university educated Nigerians in Lagos and Abuja (the previous and current capital cities respectively), our study explores gendered perspectives on the issue of remarriage after divorce to gain a deeper understanding of how customary, Islamic and statutory laws intersect. We build on previous studies (e.g. Therborn, 2004) to highlight that from the 1930s onwards, marital aspects of modern customary laws may be more patriarchal than some pre-colonial ones due to the colonial codification of customary laws in Africa. The empirical basis of our study is interviews with 24 Nigerian men and women, including female divorcees. The results suggest that what Ibrahim (2015) calls “the sociocultural penalties of divorce” are borne more heavily by women and this is exacerbated because traditional or customary laws in modern Nigeria were reshaped by colonial Christian codification. We conclude that whilst Yoruba people seem to have thwarted some of the more negative legacies of religious codification on traditional laws more than other major ethnic groups, customary laws in Nigeria still require re-codification to take on board the perspectives of African feminism.
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 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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".