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Record W307624838

Would Presuming Consent to Organ Donation Gain Us Anything but Trouble

2010· article· en· W307624838 on OpenAlexvenueaboutno aff
Mark Ammann

Bibliographic record

VenueHealth law review · 2010
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsOrgan donationHeadlineDonationMedicineLawPsychologyTransplantationPolitical scienceSurgeryAdvertisingBusiness
DOInot available

Abstract

fetched live from OpenAlex

Organ donation is often in the news, ranging from the considerable media attention following the death and subsequent donation by Australian actress Natasha Richardson to the saga of Toronto baby Kaylee Wallace and the (ultimately moot) debate over whether to donate her organs to a fellow infant patient. first long-distance kidney swap also made national headlines in June 2009. Reform of the donation system also has a way of capturing attention. Gordon Brown's attempts to implement presumed in Great Britain received consistent media coverage. (1) As the finishing touches are being added to this article, Wales is now considering the merits of changing its system to presumed consent. (2) When organ donation is discussed, current donation system is often portrayed in less than favorable light. Often times, such articles include calls for reform of our organ donation system, sometimes focused on instigating presumed consent. For instance, a recent editorial in the Calgary Herald suggests the following after a discussion of Baby Kaylee's circumstances: One solution may be to follow Spain's example and assume that the organs of anyone who dies will be transplanted unless otherwise specified in advance. This would provide a larger supply of donor organs and help reduce the possibility of a scenario like that at Sick Kids [Hospital] recurring. (3) An older headline from the Edmonton Journal reading Canada's organ-donation rate among world's worst provides less specific criticism in a much more direct manner. (4) Is system of organ donation really that bad? Is changing our system necessary for boosting our donation levels? Do we really have an unacceptably low organ donation rate? I argue that the answer to all these questions is no. This paper will attempt to defend current donation organ system. While both live and cadaveric donation are important factors to consider in this context, this paper will only take issue with the system for post mortem cadaveric organ donation. (5) Specifically, I intend to argue that (1) rate of organ donation is not as bad as portrayed, (2) presumptions regarding have limited impact on donation rates and (3) legal, political and practical factors in Canada favor the retention of our current explicit system. What is Explicit Consent vs. Presumed Consent? Current System of Explicit Consent to Cadaveric Organ Donation Organ donation legislation is within provincial jurisdiction and, as a result, there are a variety of different legislative approaches. Despite differences, however, all provinces operate on an consent (or opt in) basis. In an express model, organ donation can only occur after a potential donor has expressly consented (through registration in a donor registry, oral direction or written direction) to the removal of their organs after death. If the donor does not before their death, a surrogate decision maker is generally appointed by legislation to decide for the potential donor. Surrogate decision makers are selected in order of legislative priority, with non-estranged spouses at the top and a non-family member lawfully possessing a donor's corpse at the bottom. The key feature in an express system is that, without some positive (from the donor or surrogate decision maker), the donor will be presumed not to have consented and no organs will be removed. While a donor's to have their organs removed for transplant following death is legally binding and sufficient to authorize the harvesting of those organs, (6) in practice a potential donor's family effectively possesses a veto. Hospitals or transplant agency staff will, if a potential donor has family, request the family's permission even if the donor has already recorded consent. …

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)0.031
metaresearch head score (Gemma)0.104
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.166

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.104
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0050.033
Scholarly communication0.0130.018
Open science0.0030.005
Research integrity0.0350.035
Insufficient payload (model declined to judge)0.0090.005

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 head0.050
GPT teacher head0.372
Teacher spread0.322 · 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

Citations3
Published2010
Admission routes2
Has abstractyes

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