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Record W146523708

Subject comprehension, standards of information disclosure and potential liability in research.

2001· article· en· W146523708 on OpenAlexaffabout
Daryl Pullman

Bibliographic record

VenuePubMed · 2001
Typearticle
Languageen
FieldHealth Professions
TopicEthics in medical practice
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsDeclaration of HelsinkiInformed consentLawNuremberg trialsBioethicsResearch ethicsPsychologyPolitical scienceMedicineWar crimePsychiatryInternational lawAlternative medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

I. Introduction The history of modern research ethics can be traced to ten articles of Nuremberg Code, a response to atrocities that Nazi physicians had perpetrated upon their hapless victims in so-called experiments. Informed consent to research was first and most prominent of those ten articles. In spite of this attempt to regulate human subjects research, however, some twenty years later Dr. Henry K. Beecher published a critical survey of twenty-two research projects conducted in United States in years subsequent to Nuremberg. (1) Beecher observed that in vast majority of cases research subjects were never adequately apprised of nature of research conducted upon them. He reiterated need for informed consent as a necessary component of morally acceptable research on human subjects. At same time, however, he acknowledged that in practice it is often difficult to obtain adequately informed consent. Hence Beecher insisted on a second component in order for patients to be s afeguarded in research process, namely intelligent, informed, conscientious, compassionate, responsible investigators. (2) There can be no doubt that conduct of ethical research rests ultimately in hands of persons of integrity. Yet Beecher's own investigations indicated that we would be foolish to assume this high standard is always or usually attained. In years subsequent to Beecher's article a consensus has emerged that independent review of proposed research on human subjects is essential. This is position set forth in World Medical Association's Declaration of Helsinki, (3) and it serves as historical basis of contemporary Research Ethics Board (REB). Prior review by a duly constituted committee has become ethical sine qua non of modem human subjects research. Despite widespread implementation of REB review, however, difficulties persist with regard to matter of ensuring informed consent on part of prospective research subjects. (4) The 1980 Supreme Court decision in Reibl v. Hughes (5) established Canadian standard for informed consent to therapeutic treatment. However, leading Canadian case for consent in context of research and experimentation was established some 15 years earlier in Halushka v. University of Saskatchewan et al. (6) In Halushka Justice Hall argued that duty owed by researchers toward prospective subjects is greater than that owed by medical practitioners to their patients. (7) A stricter standard of disclosure in research context is now generally accepted in law. (8) To quote one authority on subject, it is the most exacting duty possible, requiring 'full and frank disclosure' of all risks, no matter how remote or how rare. (9) Canadian legal (10) and ethical (11) commentators continue to cite Halushka as leading case on informed consent to research. This is understandable in that it is one of few cases of this nature that has made its way through courts. (12) It is also case that established that standard for consent to research is stricter than that applied to therapy. However, it can be argued that Halushka in fact invoked a weaker standard of informed consent than that which was later applied in Reibi v. Hughes. Since so much commentary on consent to research continues to invoke Halushka, it is necessary to examine what this judgment did in fact establish, how it is related to later judgment in Reibl, and to consider combined implications of these and subsequent cases for consent to research. This paper considers what can be learned from Halushka v. University of Saskatchewan, Reibl v. Hughes and subsequent decisions (13) with regard to consent to participate in clinical trials. In particular it is argued that standard of information disclosure utilized currently in many clinical trials fails to meet strict standard set in Reibl v. …

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)0.120
metaresearch head score (Gemma)0.222
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.635

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1200.222
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0040.053
Scholarly communication0.0180.016
Open science0.0030.009
Research integrity0.0170.010
Insufficient payload (model declined to judge)0.0130.002

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 head0.161
GPT teacher head0.494
Teacher spread0.333 · 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.

Study designTheoretical or conceptual
DomainMethods
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

Citations8
Published2001
Admission routes2
Has abstractyes

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