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Record W3179758585 · doi:10.6000/1929-4409.2021.10.141

Poor Organ Donation in Vietnam: Resulting from Beliefs, Religions, and Traditional Culture? How to Promote Organ Donation and to Deal with Organ Trading from a Legal Perspective?

2021· article· en· W3179758585 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Criminology and Sociology · 2021
Typearticle
Languageen
FieldMedicine
TopicOrgan Donation and Transplantation
Canadian institutionsnot available
Fundersnot available
KeywordsOrgan donationLegislationBusinessPerspective (graphical)DonationLawOrgan transplantationOrgan cultureMedicineTransplantationPolitical scienceSurgeryBiology

Abstract

fetched live from OpenAlex

In Vietnam, organs are always in great demand while the organ supply from brain dead donors is extremely small, prompting the search for organs supplied by living people. People in need of an organ transplant either have to wait for a legally supplied organ (coming from any voluntary and non-commercial donation) or resort to an illegal supplied one (through organ trading). Therefore, increasing the number of legally supplied organs and controlling illegal source of supply are problems to be solved by Vietnam. This paper discovers whether religions, beliefs, traditional culture, and current legislation impede the organ donation or not. In addition, this paper also aims to find out legal loopholes resulting in ineffective handling of organ trading, then proposing solutions to improve the law to promote the legal supply of organs and effectively combat crimes related to organs illegally supplied by organ trading.

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)0.001
metaresearch head score (Gemma)0.004
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.003
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.033
GPT teacher head0.293
Teacher spread0.260 · 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
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

Citations1
Published2021
Admission routes1
Has abstractyes

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