Low vision care in India: a time for action! & Issues which need to be considered (plenary lecture, the 9th International Congress on Low Vision, July 10, 2008, 8:00 AM, Montreal, Canada).
Bibliographic record
Abstract
With a national population now estimated at 1.1 billion people (and growing!), it is often stated that India accounts for 1/3 of all blind and visually impaired individuals in this World! If this statement is correct, this means that there are 5-6 million visually impaired and blind individuals in India! Although certainly real progress is being made, one can reasonably ask, is the existing organizational structure designed to serve the needs of so large a number of people, and are the necessary care-providers available to provide for visual rehabilitation requirements of this very substantial cohort of affected patients? Both continuing growth and aging of the Indian population tend to challenge the capacity of that Nation to meet demands for ophthalmic services, as well as their ability to meet the visual rehabilitation requirements of this populace. Modern optometry is, in many ways, a nascent profession in India. In behalf of the large cohort of visually impaired patients, I argue that a difference can be made through effective inter-professional cooperation between emerging modern optometry and more developed ophthalmology! I hope to see an increasing role for optometry in the provision of care for the visually impaired and blind in coming years. Here, I discuss a number of issues pertinent to needs of the blind and visually impaired population, as well as means for enhancing applicable rehabilitation services.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".