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Record W2809193512 · doi:10.1080/13648470.2017.1392100

Accounting for the money-made parenthood of transnational surrogacy

2018· article· en· W2809193512 on OpenAlexaboutno aff
Ingvill Stuvøy

Bibliographic record

VenueAnthropology and Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicReproductive Health and Technologies
Canadian institutionsnot available
FundersNorges Teknisk-Naturvitenskapelige Universitet
KeywordsContext (archaeology)SociologyMonetizationSet (abstract data type)Gender studiesEconomics

Abstract

fetched live from OpenAlex

In the last decade, transnational surrogacy has attracted world-wide attention for making babies and pregnancies exchangeable with money. Involuntarily childless couples and individuals travel abroad and pay to have the desired child and to become parents. Acknowledging the importance of asking into the consequences of this monetization of reproduction, the author takes issue with universalistic assumptions about money and markets, and their presumed universal effects on social relations. Instead, it is argued that we need to explore how money works, and, by extension, how transnational surrogacy works out and becomes viable to people as a way to become parents. Putting together insights from economic sociology, and the assisted reproductive technology and parenting culture literature, the author employs the notion of accounting to grasp how people make sense of the money involved in making them parents. Based on a study involving 21 interviews with Norwegian gay and straight couples and single men and women seeking surrogacy abroad, the author explores how money is accounted for in three cases, set in three different countries; India, the United States and Canada. The analysis shows how money is accounted for in particular ways to confirm parenthood. These ways differ depending on the local context and transnational relations; ultimately making differentiated monetized parenthood. This is of significance when we try to conceptualize contemporary parenthood and how money seemingly sustains parenthood in ever more radical ways.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.517
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.046
GPT teacher head0.395
Teacher spread0.349 · 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 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

Citations20
Published2018
Admission routes1
Has abstractyes

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