“I Really Wanted to Further My Education but That Wasn’t Possible”: Out of School Experiences of Youth with Disabilities in Ethiopia, Ghana, and South Africa
Bibliographic record
Abstract
Leaving school prematurely can have lifelong repercussions, and further entrench inequity and cycles of poverty faced by youth with disabilities on the African continent. This manuscript shares the experiences of youth with disabilities in Ethiopia, Ghana, and South Africa who left education sooner than desired. It highlights the barriers leading to these educational inequalities, and facilitators that created necessary access and support systems. Method: This was a participatory research study with youth with disabilities implemented in three sites, namely, Ethiopia, Ghana and South Africa. This sample size for this paper was a total of 41 participants, which included males and females between 14–35 years of age, who self-identified as having a motor, communication, vision, and/or hearing impairment. Seven focus groups across the three sites were held. Results: Our analysis identified three key themes related to educational experiences: social environment, physical environment, and managing health challenges. Conclusion: The interdependence of relationships and support facilitated participation and inclusion in the education systems. We have framed recommendations using a feminist ethics of care, as it relates to attentiveness, responsibility, competence, responsiveness, and integrity.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".