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Record W3177146276 · doi:10.1080/13648470.2020.1865037

Weeping wombs: Leucorrhea and the chronicity of distress in Gilgit-Baltistan

2021· article· en· W3177146276 on OpenAlexaff
Emma Varley

Bibliographic record

VenueAnthropology and Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsBrandon University
Fundersnot available
KeywordsMedicineTraditional medicine

Abstract

fetched live from OpenAlex

In Gilgit, capital of the Gilgit-Baltistan region in northern Pakistan, leucorrhea - vaginal discharge known in the vernacular as safaid pani, or 'white water' - serves as both a medical diagnosis and signifier of the chronicity of the reproductive, social, and emotional burdens endured by women. While ethnomedical providers explained safaid pani as resulting from relatively benign forms of 'weakness', which required minimal dietary or ethno-botanical recourse, allopathic physicians approached discharge as evidence of numerous pathologies that necessitated protracted and sometimes also expensive treatments. Physicians' clinical assessments were not solely biomedical, but also integrated informal folk and formal ethnomedical theories of causation. Clinical diagnoses that affirmed leucorrhea as a pathophysiology substantiated women's belief that it was proof of the destructive effects of sustained social inequity, peril, and distress on the body, and the uterus in particular. Women and their treating providers recognized the power of the (dys)functional uterus to not only threaten women's reproductive wellness but also their social, marital, and familial status, which hinged on their ability to become pregnant and give birth, to sons especially. Because of the ailing uterus's expansive importance, weeping wombs served as a potent source for women's claims making and calls for attention and care.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.332
Teacher spread0.316 · 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.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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