Exploring access to government-led support for children with disabilities in Bangladesh
Bibliographic record
Abstract
While access to support for individuals with disabilities has attracted international attention, children with disabilities and their families continue to face a range of barriers that limit their timely access to the needed support, including health service. This is even worse for children with disabilities living in resource poor settings like Bangladesh. The objective of this study was to determine the extent to which families of children with disabilities have knowledge about and access to government support for their children with disabilities in Bangladesh. We employed a cross-sectional study among 393 families of children with disabilities who sought services from the Centre for the Rehabilitation of the Paralysed for their children with disabilities in Bangladesh. We used chi-square test to measure the association between categorical variables and, Mann-Whitney U-test to compare mean across different sub-groups. Overall, family members of children with disabilities have limited knowledge about and access to government support. We found a significant association between knowledge and access to government support (p<0.001). Family members with children with disabilities aged younger than six years had less access to government support (p<0.001). We thus concluded with an urgent call on government agencies and service providers to provide relevant and timely information to families of children with disabilities to enable them to access the needed support.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".