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Record W2139335589 · doi:10.1136/medethics-2012-101129

Is it ethical to invite compatible pairs to participate in exchange programmes?

2013· article· en· W2139335589 on OpenAlexafffund
Marie‐Chantal Fortin

Bibliographic record

VenueJournal of Medical Ethics · 2013
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsDisadvantageDistributive justiceTransplantationEquity (law)DonationEconomic JusticeMedicineOrgan donationKidney donationAffect (linguistics)Kidney transplantationPsychologyPolitical scienceInternal medicineLaw

Abstract

fetched live from OpenAlex

Living kidney transplantation offers the best results for patients with end-stage renal disease (ESRD). This form of transplantation is no longer restricted to genetically or emotionally related donors, as shown by the acceptance of non-directed living anonymous donors, and the development of exchange programmes (EPs). EPs make it possible to perform living kidney transplantation among incompatible pairs, but while such programmes can help increase living organ donation, they can also create a degree of unfairness. Kidney transplant recipients in the O blood group are at a disadvantage when it comes to EPs because they can only receive organs from O donors, whereas O donors are universal donors. This poses a major challenge in terms of distributive justice and equity. A way to remedy this situation is through altruistic unbalanced paired kidney exchange (AUPKE), in which a compatible pair consisting of an O blood group donor and a non-O recipient is invited to participate in an EP. Although the AUPKE approach appears fairer for O recipients, it still raises ethical questions. How does this type of exchange affect the donor/recipient gift relationship? Should recipients in compatible pairs receive a 'better organ' than the one they would otherwise have received from their intended donor? Finally, what is the role of transplant teams in AUPKE? This article will examine the organisational and ethical challenges associated with EPs and AUPKE, and compare different EP policies in countries where such programmes exist.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.543
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
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 head0.145
GPT teacher head0.442
Teacher spread0.296 · 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.

Study designNot applicable
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

Citations23
Published2013
Admission routes2
Has abstractyes

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