“A Wonderful Movie!”: The Appropriation of Entertainment Ultrasound Technology in The Netherlands
Bibliographic record
Abstract
It is now almost impossible to imagine a pregnancy in The Netherlands without one or two fetal ultrasounds. In contrast to the biomedical view of seeing ultrasound technology as a transparent window into the womb, much scholarly research in the social sciences highlights that the technology is not neutral, but has different meanings and applications depending on the context. Feminist anthropologists have mostly criticized ultrasound technology for invading the intimate experience of pregnancy and making women “invisible.” This article focuses on socalled “entertainment” ultrasounds to explore how pregnant women in The Netherlands use ultrasound technology for new, unintended purposes. Using semi-structured interviews and discourse analysis of websites of commercial ultrasound clinics, I demonstrate that many pregnant women in The Netherlands consider the ultrasound scan a positive and valuable experience that they can consciously use to feel less insecure and to relax during their pregnancy. It is argued that, in looking so closely at the structural power relations that limit women’s agency, feminist anthropologists often downplay the possible leeway that expectant mothers have. These women are not forced into doing “entertainment” ultrasound scans but are active agents appropriating the technology.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| 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".