Guest Editorial: Student Satisfaction with Experiential Learning in External Geriatrics and External Paediatrics
Bibliographic record
Abstract
The external geriatrics and external paediatric services provided by the University of Waterloo, School of Optometry and Vision Science (UWOVS) program are two examples of this type of enhanced experiential learning.Third and fourth year clinical interns have the opportunity to participate in these services.In addition to optimizing learning, these educational experiences expose students to career options and styles of practice that they might not otherwise have considered.Having optometrists pursue these avenues of service provides a significant benefit for the communities within which they practice.The external geriatrics service provides care to the geriatric population living in long term care facilities (LTC) or retirement dwellings.It is well known that the average age of the Canadian population is increasing.In 2013, 15.3% of the Canadian population was over the age of 65 and by 2030 it is projected that approximately 25% of the population will be in this age group.The proportion of older seniors (>80 years old) will also increase from 4.1% to 9.6% of the total population by 2045 or represent 39.4% of seniors.In 2011, 7.9% of seniors were living in a retirement, (LTC) or health care facility.4,5 The impact of the overall increase in representation of seniors in the population means that there will be an increasing need to provide service for this population within retirement dwellings.Vision impairment is 3 to 15 times higher in seniors who reside in a LTC facility or retirement home than seniors residing in the community.6 This is consistent with the higher prevalence of ocular disease in those residing in a LTC facility or retirement home.7 A study by Labreche et al 8 of seniors residing in LTC facilities or retirement communities in the Waterloo region confirmed that the prevalence of AMD is higher (41.2%) than published data for those in the general population over the age of 80 years of age (13.6%).9 At a more basic level, it has been found that approximately 37% of those residing in a facility would benefit from suitable correction of refractive error.10 Visual impairment has been shown to lead to an increased C a n a d i a n J o u r n a l o f O p t o m e t r y | R e v u e C a n a d i e n n e d ' O p t o m é t r i e
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.014 | 0.011 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".