MétaCan
Menu
Back to cohort

THE ETHICS OF INTERCOUNTRY ADOPTION: WHY IT MATTERS TO HEALTHCARE PROVIDERS AND BIOETHICISTS

2010· article· en· W2154129618 on OpenAlexaff
Sarah Jones

Bibliographic record

VenueBioethics · 2010
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsUniversity of Toronto
FundersUniversity of Otago
KeywordsHealth careReproductionPublic relationsEthical issuesPosition (finance)BusinessSociologyPolitical scienceLawEngineering ethics

Abstract

fetched live from OpenAlex

The goal of this paper is both modest and ambitious. The modest goal is to show that intercountry adoption should be considered by ethicists and healthcare providers. The more ambitious goal is to introduce the many ethical issues that intercountry adoption raises. Intercountry adoption is an alternative to medical, assisted reproduction option such as in vitro fertilization (IVF), intracytoplasmic sperm injection, third party egg and sperm donation and surrogacy. Health care providers working with assisted reproduction are in a unique position to introduce their clients to intercountry adoption; however, providers should only do so if intercountry adoption is ethically equal or superior to the alternatives. This paper first presents a brief history of intercountry adoption. The second section compares intercountry adoption with medical alternatives. The third section examines the unique ethical challenges that are not shared by other medical alternatives. The final section concludes that it is simplistic for a healthcare provider to promote intercountry adoption unconditionally; however, in situation where intercountry adoption is practiced conscientiously it poses no greater ethical concern than several medical alternatives. This conclusion is preliminary and is intended as a start for further discussion.

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)0.058
metaresearch head score (Gemma)0.078
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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.058
Threshold uncertainty score0.307

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.078
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0090.044
Scholarly communication0.0110.015
Open science0.0010.007
Research integrity0.0130.017
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 head0.098
GPT teacher head0.405
Teacher spread0.308 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueBioethicsSame topicReproductive Health and TechnologiesFrench-language works237,207