US “contracted surrogates”. Between gift-giving and help narratives
Bibliographic record
Abstract
In this paper, I present findings from two ethnographic research conducted on US surrogacy within two different fertility clinics based in Southern California (2014-2016; 2017-2020). The paper analyzes the experiences of fifty US surrogates and some reproductive industry employees, to show new trends in framing surrogacy in the US over the last decade. Existing sociological and anthropological studies on US surrogacy focused on new forms of kinship highlighting the gift-giving theory as a key concept with which to analyze contemporary surrogacy. The aim of this contribution is to answer the following questions: how and for what purposes do surrogates evoke gift categories when they do, and what does it mean when they don’t? My article will reveal new trends especially regarding the populations involved in a surrogacy journey (i.e., more African American, and Hispanic surrogates and fewer White ones), a lack of communication and relationship between parties, and new analytical categories to read US surrogacy (surrogates use the concept of help more readily than ideas around gift-giving).
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".