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Record W1571175991 · doi:10.1017/cbo9780511973536

Organ Shortage: Ethics Law and Pragmatism

2011· book· en· W1571175991 on OpenAlexaboutno aff
Anne‐Maree Farrell, David Price, Muireann Quigley

Bibliographic record

VenueResearch Explorer (The University of Manchester) · 2011
Typebook
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsOrgan donationEconomic shortageTransplantationPopulationPolitical scienceWrightLawSociologyMedicineSurgeryHistory

Abstract

fetched live from OpenAlex

Part I. Setting the Scene: 1. Organ shortage: principles, pragmatism and practice Anne-Maree Farrell, David Price and Muireann Quigley 2. Does ethical controversy cost lives? Margaret Brazier and John Harris Part II. Current Issues Affecting Organ Shortage: 3. Organ donation and transplantation: meeting the needs of a multi-ethnic and multi-faith UK population Gurch Randhawa 4. Educating the public to encourage organ donation? Mairi Levitt 5. Bereavement, decision-making and the family in organ donation Magi Sque and Tracy Long-Sutehall Part III. Strategies for Addressing Organ Shortage: 6. Incentivising organ donation Muireann Quigley 7. Making the margins mainstream: strategies to maximise the donor pool Antonia Cronin 8. The allocation of organs: the need for fairness and transparency Phil Dyer and Sheelagh McGuinness 9. Ante-mortem issues affecting deceased donation: an ethico-legal perspective John Coggon and Paul Murphy Part IV. Comparative Perspectives: 10. Institutional organisation and transplanting the 'Spanish model' Monica Navarro-Michel 11. Kidney donation: lessons from the Nordic countries Salla Loetjoenen and Nils Persson 12. Organ donation and transplantation: the Canadian experience Linda Wright and Diego S. Silva 13. Systematic increases in organ donation: the United States experience Alexandra K. Glazier Part V. Current Reform and Future Challenges: 14. Negotiating change: organ donation in the UK Bobbie Farsides 15. Addressing organ shortage in the European Union: getting the balance right Anne-Maree Farrell 16. Promoting organ donation: challenges for the future David Price.

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)0.022
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.116

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0100.053
Scholarly communication0.0150.010
Open science0.0020.009
Research integrity0.0120.020
Insufficient payload (model declined to judge)0.0070.003

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 head0.151
GPT teacher head0.326
Teacher spread0.175 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations19
Published2011
Admission routes1
Has abstractyes

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