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Record W3037436764 · doi:10.1055/s-0040-1712115

Assumptions about Decision-Making Capacity and Aphasia: Ethical Implications and Impact

2020· article· en· W3037436764 on OpenAlexaff
Aura Kagan, Elyse Shumway, Sheila MacDonald

Bibliographic record

VenueSeminars in Speech and Language · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsAphasiaCompetence (human resources)ObligationPsychologyCommunicative competenceProcess (computing)Engineering ethicsComputer scienceSocial psychologyCognitive psychologyPedagogyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

This article explores the issue of aphasia and decision-making within the context of clinical ethics and patient rights. The cases described illustrate the danger of making assumptions about the inherent competence of people with aphasia and the life-altering consequences if no attempt is made to "accommodate" or support communication when competence may be masked by aphasia. Speech-language pathologists have a moral obligation and a key role to play in providing communication support that may serve to reveal a person's intact capacity to make specific decisions, as well as in supporting the steps involved in the decision-making process. This role also extends to providing guidance, education, and training for others involved in evaluating the decision-making capacity of people with aphasia. Communication support strategies useful at each stage of the decision-making process are detailed.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.133
metaresearch head score (Gemma)0.215
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.133
Threshold uncertainty score0.701

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1330.215
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0120.105
Scholarly communication0.0150.019
Open science0.0030.018
Research integrity0.0150.022
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.054
GPT teacher head0.478
Teacher spread0.424 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2020
Admission routes1
Has abstractyes

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