Fatness and the Maternal Body: Women's Experiences of Corporeality and the Shaping of Social Policy
Bibliographic record
Abstract
FATNESS AND THE MATERNAL BODY: WOMEN'S EXPERIENCES OF CORPOREALITY AND THE SHAPING OF SOCIAL POLICY Maya Unnithan-Kumar and Soraya Tremayne, Eds. New York & Oxford: Berghahn Books, 2011 Fatness and the Maternal Body: Women's Experiences of Corporeality and the Shaping of Social Policy is a collection of articles which demonstrate the significance of fatness through different cultures. It is the result of a series of workshops and seminars facilitated by the Fertility and Reproduction Studies Group (FRSG) at the Institute of Social and Cultural Anthropology hosted by the University of Oxford in 2006. This collection focuses on cultural socialization and perspectives of and their links to reproduction, health risk, obesity, and status. The articles explore data from the United Kingdom, Africa, and India, presenting the differing cultural standards placed on fatness of the female body (pre and post-natal), and the direct relationship to obesity, health, social and political status, and wealth. This compilation explores what it means to be (socially, culturally, and medically). The editors take care to note that there is unfortunately no discussion of male fatness, and its effects on reproductive health in this collection, it being a highly under-researched area. The perspectives of fatness that are presented are culturally and socially linked to their country of origin. In the United Kingdom, for example, the articles depict mothers who are clinically overweight or obese who prefer terminology such as big boned, and relate their size to genetics. The associated social stigma discussed is that they do not recognize healthy nutrition, are from lower income housing, and will have unhealthy fat babies because of their poor dietary routines. The risks of diabetes and low birth weight babies are outlined in these articles also. The overarching medical assessment is that something must be initiated to stop the perpetuation of the obesity cycle. The problem raised is that there is no generic answer as to when an interruption of said cycle serves the patient/public best. As one of the study subjects from Chapter 2 asserts, overweight bodies, through pregnancy, are replaced by a thriving, glowing and healthy body [which] was meant to eat, allowed to eat. The reader views this subject who recognizes that she shouldn't perhaps eat as much as she does, or as poorly, but is relishing pregnancy because food is no longer negative. This perspective contrasts that of the African tribes studied for the workshop/seminar series. …
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| 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".