The Evaluation of Capacity to Make Admission Decisions: Is it a Fair Process for Idividuals with Communication Barriers?
Bibliographic record
Abstract
In Ontario the Health Care Consent Act protects the rights of competent patients to understand an alternate discharge destination and to consent to such discharge plans. Social work case managers evaluate the capacity of patients to refuse or accept admission to long-term care facilities by administrating the ‘Capacity to Make Admission Decisions’ questionnaire. The evaluation is a framework to reveal the patient's ability to understand and appreciate a decision. This article will show that the current capacity evaluation is not a fair process for people with communication barriers arising from stroke, progressive neurological diseases or English as a Second Language (ESL). Critical thinking and competency can be preserved but is masked both by the communication barrier and by an evaluation process that is inaccessible to many. This article will also proffer solutions in order to preserve the rights of this particularly vulnerable population.
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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 | 0.154 | 0.334 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".