Lost boys, invisible girls: stories of Sudanese marriages across borders
Bibliographic record
Abstract
Forced migration challenges and changes gender relations. The transnational activities of refugees resettled in the West create gender asymmetries among those who stay behind. This article explores the transnational marriages of young southern Sudanese women (‘invisible girls’), who either stayed in Sudan or remained in refugee camps in Kenya, to Sudanese men who were resettled to America, Canada or Australia (‘lost boys’). Incorporating gender as a relational category into the analysis of transnational practices that migrants and refugees engage in is important. The article argues that there is a need to put feminist analysis at the centre of transnational processes resulting from (forced) migration. It looks at the connections between different geographical locations, the impacts of the migration of young refugee men on bridewealth and marriage negotiations and the gender consequences for young women, men and their families. It is argued that transnational activities, such as marriage, contest, reconfigure and reinforce the culturally inscribed gender norms and practices in and across places. Transnational marriage results in ambiguous benefits for women (and men) in accessing greater freedoms. Anthropological analyses of marriage need a geographical focus on the transnational fields in which they occur. The article seeks to deepen understanding of the nuanced gendered consequences of transnationalism. It shows how gender analysis of actions taken across different locations can contribute to the theorisation of transnational studies of refugees and migrants.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.038 | 0.015 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".