Out-of-School Vision Screening in North India: Estimating the Magnitude of Need
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: Few studies have examined the extent to which school-based vision screening is sufficient to achieve universal coverage among school-aged children in India.Method: A rural administrative region (‘Block’) was examined. Government records provided the total population of the rural Block, the proportion of school-aged children, and school authorities in the Block provided the number of enrolled students. Absenteeism was measured directly by visiting a representative sample of the schools. The proportion of the school age population found in school was assessed using the indicator, Effective Coverage (EC): the proportion of children attending school divided by the total population of school-aged children in the region.Results: In the rural block, the proportion of children actually enrolled in school was 52% of the school-aged population, with 68% of them attending school. Therefore, EC was 35% (68% of the 52% enrolled).Conclusion: Population coverage by school vision screening would be unacceptably low in a rural setting in northern India. Out-of-school vision screening programs are needed in these rural settings to achieve universal coverage.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it