Linking schools, universities, and businesses to mobilize resources and support for career choice and development of students who are visually impaired
Bibliographic record
Abstract
This study documents how linking schools, universities, and local organizations can make school curriculum more relevant for career development for students who are visually impaired. Two schools, one for the visually impaired with students aged 4–19 years and another school for students aged 11–19 years who have severe or profound learning difficulties, were part of the collaboration, along with local university students who were teachers in training. Outcomes included new curriculum material for use in public schools to sensitize sighted students on visual impairment. The project also initiated employment apprenticeships for two students who are visually impaired. Our findings suggest that we can educate multiple groups of students simultaneously while building stronger ties between schools, universities, and local public and private employers. Using an outreach approach results in building relationships that facilitate education and employment for students who are visually impaired. St. Vincent’s School obtained consent for all participants in this study and participants chose to be identified, rather than have a pseudonym used.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".