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Record W4224998209 · doi:10.1177/08404704221091176

Consent, capacity, and client sexuality policies in healthcare

2022· review· en· W4224998209 on OpenAlexaff
Jeremy Butler, Dave Langlois

Bibliographic record

VenueHealthcare Management Forum · 2022
Typereview
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsUniversity of TorontoQueen's University
Fundersnot available
KeywordsHuman sexualityHealth careBusinessNursingMedicinePolitical scienceLaw

Abstract

fetched live from OpenAlex

Healthcare organizations face significant ethical complexity when developing policies related to the sexual activities of clients within their facilities. On one hand, admission to healthcare facilities should not require clients to abstain from all sexual activity. On the other hand, clients' sexual activities within facilities have implications for other people, and many clients may be at risk of sexual mistreatment. In response, organizations may be tempted to approach their clients' decisions about sexual activity on the model of decisions about medical treatment. In this article, we argue that this approach is more ethically problematic than it may first appear. We review asymmetries between the decisional contexts of medical treatment and sexual activity and argue that those asymmetries generate ethical issues for any policy that treats clients' decisions about sex as analogous to decisions about treatment. We also offer suggestions for the development of ethically justifiable policies related to client sexuality.

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)0.024
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.024
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.066
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0010.007
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.404
GPT teacher head0.576
Teacher spread0.172 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2022
Admission routes1
Has abstractyes

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