“It Would Help to Know What Our Children Are Taught”: A Cry of the Voiceless Parents Pertaining School Curriculum Development
Bibliographic record
Abstract
School education ministries in many countries, globally, purportedly advocate for parental involvement in the education of their children. Accordingly, associations that are designed, at least on paper, to accommodate parents in school related issues exist in many schools world-wide. In South Africa, where the current study was conducted, these structures are known as School Governing Bodies (SGBs). Like their counterparts, elsewhere, parents in SGBs discharge responsibilities, such as recruitment and selection of school personnel, financial management and enforcing learner discipline. This study was prompted by the paucity of research regarding parental involvement in curriculum development. Accordingly, this qualitative case study employed one-on-one interviews with parents who were members of SGBs in three schools in the KwaZulu-Natal province of South Africa. The aim was to probe their perceptions regarding their role on curriculum issues. Like numerous studies conducted previously concerning the role of parents at school, the findings of this research suggest that parents are marginalised when it comes to curriculum issues. The research recommends that more studies of similar nature be conducted and that education authorities must strive to empower parents to enable them to participate meaningfully in curriculum issues.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.020 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".