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Record W2772204907 · doi:10.1177/1073110517720649

Covering It Up? Questions of Safety, Stigmatization, and Fairness in Covert Medication Administration

2017· article· en· W2772204907 on OpenAlexfundno aff
Christy Simpson

Bibliographic record

VenueThe Journal of Law Medicine & Ethics · 2017
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsnot available
FundersHealth Canada
KeywordsCovertAdministration (probate law)Relevance (law)Vulnerability (computing)Perspective (graphical)Health careEconomic JusticePsychologyMedicinePublic relationsPolitical scienceComputer securityLawComputer science

Abstract

fetched live from OpenAlex

This paper examines the practice of covert medication administration from an organizational ethics perspective. This includes consideration of vulnerability and stigmatization, safety, and fairness (justice) in terms of the culture of health care organizations and the relevance of policies and processes in relation to covert medication administration. As much of the discussion about covert medication administration focuses on patients and health care providers, this analysis aims to help expand the analysis of this practice.

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)0.081
metaresearch head score (Gemma)0.211
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 score0.081
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0810.211
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.054
Scholarly communication0.0060.012
Open science0.0010.006
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0010.000

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 head0.209
GPT teacher head0.559
Teacher spread0.350 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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