The Inevitable Challenge of Ethical Dilemmas in Optometry, Part 1: When Confidentiality is Tested
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
Healthcare professionals often face ethical dilemmas, which arise when two ethical principles conflict. Despite the potential for psychological consequences, no study has examined ethical dilemmas in the field of optometry. Objective. This article is the first in a series of three pertaining to a joint study that aimed to identify and describe the ethical dilemmas faced by optometrists. Method. An online survey sent to 1,393 optometrists asked them about various categories of ethical dilemmas. Unlimited space was provided for explanations. Results. Each of the 22 ethical dilemmas proposed had previously been encountered by between 3.75% and 67.9% of the 240 respondents. This first article reports that ethical dilemmas involving confidentiality are varied and those pertaining to the filling out of driver’s licence forms had previously affected 40% of the participants. Conclusion. Optometrists regularly face tough ethical decisions for which knowledge of the legislation and regulations alone is insufficient. The results will be revealed in the next two articles in this series, with the last one broaching the discussion of how to optimize the management of ethical issues in the field of optometry.
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 | 0.021 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.011 |
| Insufficient payload (model declined to judge) | 0.017 | 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