Secondary school learners’ understanding of Namibian boys’ underachievement and under-participation in education
Bibliographic record
Abstract
To understand the manifestations of gender disparity in academic achievement between boys and girls, we conducted the Namibian boys’ underachievement in education study. In this article we present data from this study on secondary school learners’ understanding of the disparity. Using a pragmatic parallel mixed methods research design, systematic and criterion sampling techniques, we collected data by administering structured questionnaires to 4659 learners. We also conducted focus group discussions with purposefully selected learners. Some boys performed worse than girls and under-participated in education because they withdrew from learning activities, believed they could do without education, they were not interested in education, dropped out of school and did not actively participate in learning activities. Several parents undermined their sons’ educational achievement during socialization by giving them too much freedom to roam while strictly controlling the behaviour of their daughters; allowing their sons to abuse alcohol and drugs; not giving their sons responsibilities at home; not being concerned of their sons’ education, misconduct, and welfare. We have recommended that schools should establish boys’ academic intrinsic achievement motivation programmes by addressing their dysfunctional motivational attitudes, beliefs, and behaviours. Such programmes should also attend to the boys’ adverse external motivational factors such as negative peer pressure and lack of supportive family and community environments.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".