Effects of Child Abuse on the Academic Performance of Primary School Learners in the Manzini Region, Swaziland
Bibliographic record
Abstract
The purpose of this study was to investigate the effects of child abuse on the academic performance of primaryschool learners in the Manzini Region of Swaziland. The study was qualitative in nature and utilised thephenomenological research design. The target population were the abused learners from the Manzini primary schools.Data were collected from 15 abused learners and their class teachers in four schools. The critical case purposivesampling method was used to select these schools. Thus, only those schools that had abused learners wereselected.Semi-structured interviews focus group discussion and document analysis were used to collect data. Thefindings showed that a majority of the abused learners underperformed as a result of abuse andbecame suspiciousofevery person around them and this had a negative bearing to their academic performance. Some became antisocialand adopted a misdirected rancorous attitude to everyone around them. Thus in the main, the study concludes thatchild abuse affects the academic performance of learners at primary school level. Based on the findings, the studyrecommends that the stakeholders; parents, school administrators and teachers included, should work hand-in-hand inhandling abused learners in order to help them overcome their challenges and improve theiracademic performance andsocial life. In addition to that, the relevant ministries (Police, Child and Social Welfare and the Ministry of Educationand Training) should assist in curbing child abuse at grassroots level.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".