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Record W3003807609 · doi:10.1111/josi.12371

Fat Reproductive Justice: Navigating the Boundaries of Reproductive Health Care

2020· article· en· W3003807609 on OpenAlex
Andrea LaMarre, Carla Rice, Katie Cook, May Friedman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Social Issues · 2020
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsToronto Metropolitan UniversityWilfrid Laurier UniversityUniversity of Guelph
FundersCanadian Institutes of Health Research
KeywordsThematic analysisFertilityReproductive healthStigma (botany)Health careEconomic JusticePregnancyPsychological resilienceShameNarrativeAssisted reproductive technologySocial stigmaPsychologyQualitative researchNursingMedicineSocial psychologyPopulationSociologyFamily medicinePolitical scienceEnvironmental healthHuman immunodeficiency virus (HIV)PsychiatryInfertility

Abstract

fetched live from OpenAlex

Abstract In this paper, we explored the experiences of people in larger bodies seeking fertility and/or pregnancy care through a reproductive justice lens, integrating an understanding of weight stigma with an understanding of who has access to reproductive technologies, who is “allowed” to become pregnant, and the discourses that surround pregnancy. We conducted a thematic analysis of the narratives of 17 participants who had been labeled “overweight” or “obese” while pregnant and/or seeking reproductive health care related to fertility and/or pregnancy. Participants’ narratives speak to experiences of being surveilled and controlled in medical settings; this surveillance and control negatively impacted their access to desired care. In order to receive the kinds of care they wanted, many participants had to become self‐advocates. This self‐advocacy speaks to resistance and “resilience”; we discuss how individualizing “resilience” represents an incomplete solution to navigating the shaming and blaming encounters participants experienced with healthcare providers. We argue for health care that is more caring and responsive to the needs of diverse individuals who are or who are seeking to become pregnant.

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.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
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 head0.098
GPT teacher head0.515
Teacher spread0.418 · 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