Psychosocial challenges of children with disabilities in Sekhukhune District, Limpopo province of South Africa: Towards a responsive integrated disability strategy
Bibliographic record
Abstract
Background: Disability, and everything it encompasses, presents major challenges to individuals, families and communities worldwide. Children with disabilities (CWD) are marginalised and excluded in most societies. Discrimination and prejudice towards CWD are compounded by poverty, lack of essential services and support and sometimes a hostile and inaccessible environment. Objectives: The study sought to examine the psychosocial challenges experienced by CWD in the Sekhukhune district of Limpopo province, South Africa. Based on the identified, articulated and expressed challenges, the study sought to recommend improvement of the existing Integrated National Disability Strategy (INDS) for greater responsiveness to the needs of CWD at both provincial and local levels. Method: The interpretivist qualitative mode of enquiry was the chosen methodology for this study. Phenomenology and descriptive research designs guided the study. Purposive sampling was employed, and data were collected from 36 participants using three triangulated methods: individual in-depth interviews, focus group discussions and key informant interviews. Thematic data analysis was used to analyse data. Results: The findings revealed that CWD in Sekhukhune experienced numerous challenges which affected their social functioning, development and general well-being. Aggravating factors included stigma, labelling and discrimination; disability-specific discrimination and bullying; exclusive education; sexual exploitation; lack of governmental support and poor implementation of disability-specific policies, amongst others. Conclusion: The provisions of the INDS to promote inclusion, integration, mainstreaming and equitable access to resources and services remained an ideal rather than a reality for CWD in Sekhukhune.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".