Arranged Marriage: Change or Persistence? Illustrative Cases of Nigerians in the USA
Bibliographic record
Abstract
It is common for parents/families in traditional settings, whether in Africa or China, to pair their children/members in marriage often without their consent. This specific mate selection practice, arrangement, is used to designate marriages in these settings: the so-called arranged marriages. Observations about this mate selection practice are then posited as conclusive evidence of change in these marriages. This paper attempts an exploratory clarification of marriages in traditional Africa in two ways. First, it uses the marriage system of the Okrikans to reveal that arranged and non-arranged marriages coexist, each administered by and organized around distinct institutions, with differing consequences for family membership, inheritance and other important issues. Second, it breaks down traditional marriage into it components, and using cases to illustrate each, shows that the purported change coexists with persistence. The resistance observed with our case also seems to point to a dynamic in the immigrant/homeland interchange that has not been adequately explored.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".