Poverty, Gender and Primary Education: Experiences of Learners in Elandskop, KwaZulu Natal
Bibliographic record
Abstract
This article discusses the interconnectedness of poverty and gender and learning at primary school level in KwaZulu Natal Province of South Africa. A qualitative study was conducted in two schools in the poverty stricken Elandskop area where data were collected using in-depth face-to-face interviews from purposely selected participants comprising of learners, educators and the headmasters. The aim was to analyse how male and female learners experience poverty, gender role socialisation and the effect on children’ bio-psychosocial health of both sexes. While the findings of the study revealed that poverty and gender socialisation of boys and girls have bio-psychosocial negative influences on them, the gender dimension of poverty had the most negative influence on girls. It was found that primary school learners grapple with coping mechanisms when confronted with poverty coupled with limited family and professional support. Gendered family roles and oppressive religious beliefs have been found to have influence on early marriages and teenage pregnancies resulting in school dropouts. The findings of the study imply that school social work is vehemently lacking yet necessary in schools in the area to assist educators in addressing the psychosocial ill-health of learners which educators are less equipped to professionally handle. The study recommends appropriate bio-psychosocial interventions early in the lives of learners to curtail lifelong developmental predicaments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".