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Record W4284879357 · doi:10.15273/jue.v12i2.11408

“A Wonderful Movie!”: The Appropriation of Entertainment Ultrasound Technology in The Netherlands

2022· article· en· W4284879357 on OpenAlexvenueno aff
Roos Metselaar

Bibliographic record

VenueJournal for Undergraduate Ethnography · 2022
Typearticle
Languageen
FieldMedicine
TopicPrenatal Screening and Diagnostics
Canadian institutionsnot available
Fundersnot available
KeywordsAppropriationEntertainmentContext (archaeology)Agency (philosophy)SociologyFlexibility (engineering)Gender studiesPolitical scienceSocial scienceHistoryEpistemologyLaw

Abstract

fetched live from OpenAlex

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.022
GPT teacher head0.299
Teacher spread0.277 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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