Marriage and Cohabitation in South Africa: An Enriching Explanation?
Bibliographic record
Abstract
Patterns of marriage and family formation in South Africa have changed dramatically in recent years. Many studies have indicated that marriage patterns and changes in family structure can be attributed to economic and social changes. However, the role of cultural norms and attitudes towards marriage and cohabitation across different social locations is under-researched. Using survey data from the 2005 South African Social Attitudes Survey, we investigate the extent to which structural variables and cultural attitudes towards marriage and cohabitation predict the likelihood of such transitions. In common with other research findings, we find that structural variables such as age, gender, employment status and location were significant predictors of marriage. However the findings also indicate that cultural attitudes, when examined in conjunction with sociodemographic factors, explains more of the changes in coupling in South Africa. In particular, individuals who cohabit as a means of preparing for marriage are significantly more likely to get married at some point in the future. We argue that explanations of low marriage rates in South Africa cannot exclude the cultural context of rules and norms governing coupledom.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".