Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".