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Record W3124556017

There Will Be Sharing: Population Biobanks, the Duty to Inform and the Limitations of the Individualistic Conception of Autonomy

2014· article· en· W3124556017 on OpenAlexvenueaboutno aff
Ma’n H. Zawati

Bibliographic record

VenueHealth law journal · 2014
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyPaternalismDutyHarmPsychologyLawMedicineLaw and economicsSocial psychologyPolitical scienceSociology
DOInot available

Abstract

fetched live from OpenAlex

'Data! Data! Data!' he cried impatiently. 'I can't make bricks without clay.' --Sherlock Holmes (in Arthur Conan Doyle, The Adventure of the Copper Beeches) INTRODUCTION The principle of autonomy has been the cornerstone of the physician's duty to inform ever since paternalistic practices receded in the second half of the 20th century. (1) In the past, physicians were authorized to withhold relevant information in an effort to protect their patients from harm. (2) With the advent of comparative judgment, however, physicians were encouraged to consider whether withholding information [would] result in less harm on balance than divulging it. (3) Eventually, became a central feature of the principle of autonomy. Practically speaking, the principle of autonomy in the medical field translated to the right (of a patient) to make an informed decision free from unjustified interference by others. (4) According to one conception, to respect autonomy is: [...] to give weight to autonomous persons' considered opinions and choices while refraining from obstructing their actions unless they are clearly detrimental to others. To show lack of respect for an autonomous agent is to repudiate that person's considered judgments, to deny an individual the freedom to act on those considered judgments, or to withhold information necessary to make a considered judgment, when there are no compelling reasons to do so. (5) Based on this principle, the less an individual is expected to benefit therapeutically from a procedure, the higher the duty to inform becomes. This is true for cosmetic surgery, organ donation and non-therapeutic research. (6) In research, Canadian courts have maintained that participants are entitled to a and frank disclosure (7) and that researchers' duties in that regard are as great, if not greater, than the duties owed by physicians in the clinical setting. (8) The increasingly longitudinal and international nature of research is challenging the feasibility of maintaining such an expansive duty to inform. (9) As researchers rely less on active human participation, and more on cutting-edge technologies that generate vast amounts of data, (10) the parameters of the traditional duty to inform look increasingly porous. This is particularly true for population biobanks, which aim to study data and samples collected on a large population scale and over a long period of time. (11) In these large-scale projects, participants are informed that their data and samples will be used to establish biobanks as resources for future research in health and genomics. (12) It is very difficult to provide full in the context of a biorepository for future, unspecified research by as-yet unnamed researchers. Much ink has been spilled in the last decade on the type of consent required for these population projects. Indeed, many have debated whether or not broad consent--a model increasingly used by population studies satisfies the legal requirements of informed consent. (13) Others have focused on operational matters, examining the governance and practicability of both specific and broad consent approaches to population biobanks. (14) In contrast, this article delves deeper into the reasons why many population biobanks have resorted to broad consent and why the current legal duty to inform requirements might be inimical to such projects (in particular) and research (in general). As will be detailed later in this text, population biobanks are limited in terms of what information they can provide to research participants during the consent process. On the one hand, they are increasingly encouraged to share their findings by providing access to their repositories, but on the other hand, they are unable to provide participants with full about the future use of their data and samples at the time of recruitment. …

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.501
GPT teacher head0.537
Teacher spread0.037 · 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 teacher head, 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

Citations7
Published2014
Admission routes2
Has abstractyes

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