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Record W1990696347 · doi:10.1080/00224499.2012.688226

Medicalizing Reproduction: The Pill and Home Pregnancy Tests

2012· article· en· W1990696347 on OpenAlexaff
Andrea Tone

Bibliographic record

VenueThe Journal of Sex Research · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies on Reproduction, Gender, Health, and Societal Changes
Canadian institutionsMcGill University
Fundersnot available
KeywordsPillPregnancyPregnancy testMedicineMedicalizationUnintended pregnancyFamily planningHormonal contraceptionPopulationGynecologyFamily medicineObstetricsNursingEnvironmental healthPsychiatryResearch methodology

Abstract

fetched live from OpenAlex

This article explores one chapter in the history of medicalization through a focused study of oral contraceptives and home pregnancy tests. Each commercially successful in developed nations and both decades old (the Food and Drug Administration approved oral contraceptives in 1960 and home pregnancy tests in 1977), these reproductive technologies created the first pharmaceutical mega-market comprised of young, healthy, sexually active, heterosexual women. Examining the discrete, but interconnected, histories of both products, this article explores how the Pill's popularity and profitability medicalized and feminized contraception, encouraging pharmaceutical companies to invest in the development of patented variants of hormonal contraception and creating a means by which the under-used Pap smear could be introduced to a population that had previously resisted it. Home pregnancy tests, too, had unintended consequences. Designed to shield the detection of a pregnancy from a "medical gaze," the test's widespread use encouraged women to become medical patients at an earlier stage of their pregnancy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.997
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.022
Scholarly communication0.0020.004
Open science0.0000.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.287
GPT teacher head0.389
Teacher spread0.102 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations52
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Sex ResearchSame topicHistorical Studies on Reproduction, Gender, Health, and Societal ChangesFrench-language works237,207