Girls’ Familial Responsibilities and Schooling in The Gambia
Bibliographic record
Abstract
Like many countries in the developing world gender inequity remains a staggering problem in The Gambia, particularly at the secondary school level. In this study, we focus on the relationship between girls’ education and heavy domestic workloads, herein referred to as girls’ familial responsibilities. We explore this topic in relation not only to performance but also to the value that girls assign to schooling at the post-primary level through the use of a qualitative-inductive phenomenological-approach, mixed with descriptive survey. Findings from this study enabled us to gain a more nuanced snapshot of how, in practice, familial responsibilities can work against the goal of gender equality in and through formal education. More specifically, we find that although access to girls’ schooling has improved in The Gambia, there is still a profound tension between the values parents assigned to female education and the gender socialization of the girl child in preparation for their socially expected future roles as mothers and care takers of their families. We conclude from the data that girls are allowed to attend formal schooling, but they are expected to remain feminine in and out of formal schooling spaces. Arguably, the goal for girls to remain feminine has an immediate negative effect on their schooling performances and lasting consequences on the ways they construe their opinions and values about their gender roles, social statuses and future employment capabilities.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".