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Record W4281773004 · doi:10.1177/00207152221097600

Emerging “repronubs” and “repropreneurs”: Transnational surrogacy in Ghana, Kazakhstan, and Laos

2022· article· en· W4281773004 on OpenAlexvenueaboutno aff
Andrea Whittaker, Trudie Gerrits, Christina Weis

Bibliographic record

VenueInternational Journal of Comparative Sociology · 2022
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsSecrecyDestinationsWork (physics)ChinaScale (ratio)NationalityGeographyBusinessPolitical scienceEconomic geographyImmigration

Abstract

fetched live from OpenAlex

In this article, we offer an analysis of the development of “repronubs”: less-known locations offering small-scale, niche cross-border gestational surrogacy or surrogacy services for a regional market. This analytical category of “repronubs” is useful to describe the formation of the industry from small local sites to those offering cross-border services. Based on our work in these locations, we compare the markets, regulatory contexts, and organization of the industry in Ghana, Kazakhstan, and Laos, focusing on the “repropreneurs” or surrogacy facilitation agents as pivotal in the emergence of these sites. These “repronubs” highlight the surrogacy trade between countries of the Global South and are established next to or instead of the more well-known North–South destinations. We document how surrogacy itself is increasingly stratified between higher cost and better-regulated environments such as in certain states of the United States or Canada and lower cost, less well regulated, and regionally focused environments in the settings we describe. These locations are characterized by poor or liberal regulations, the existence of local in vitro fertilization (IVF) expertise, and the emergence of local repropreneurs driving the trade using their social networks. The growth of demand from China and the growing affluent middle class in Africa is creating further markets for such regional “nubs.” Studying surrogacy in such locations is made difficult by the secrecy and confidentiality surrounding it.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.385
Teacher spread0.336 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations18
Published2022
Admission routes2
Has abstractyes

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