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Record W2166292493 · doi:10.29173/pandpr19853

Living with Bodily Changes after Weight Loss Surgery - Women’s Experiences of Food and "Dumping"

2012· article· en· W2166292493 on OpenAlexvenueno aff
Karen Synne Groven, Gunn Engelsrud, Målfrid Råheim

Bibliographic record

VenuePhenomenology & Practice · 2012
Typearticle
Languageen
FieldMedicine
TopicBody Contouring and Surgery
Canadian institutionsnot available
FundersNorwegian Fund for Post-Graduate Training in Physiotherapy
KeywordsFeelingSituatedDilemmaLived experiencePsychologyGastric bypassWeight lossNorwegianSocial psychologyMedicinePsychoanalysisObesityEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

In this article we explore women’s experiences of “dumping” following weight loss surgery. The empirical material is based on individual interviews with 22 Norwegian women. To further analyze their experiences, we build primarily on the phenomenologist Drew Leder`s notion of the “inner body.” Additionally, Simone de Beauvoir and Merleau-Ponty’s perspectives of the lived body occupy a prime framework for shedding light on different dimensions of bodily changes. The following three core themes were identified: Experiences of illness in conjunction with eating; Learning to relate to changes in the inner body and; Feelings of losing and regaining control. In different, though interconnected ways, these themes encompass an ongoing challenge in the women’s lives after the surgery: namely their efforts to establish new eating habits while at the same time working hard to relate to their changed and changing inner body, and especially to the phenomenon of “dumping”. The results points to a dilemma: namely that the gastric bypass procedure is an operation that irreversibly alters the anatomy and physiology of a healthy stomach, whereas the individual’s eating habits cannot be situated in or reduced to a particular organ, but are endemic to the lived body and its history. This insight might be of importance in the understanding of the complexity of the changes and challenges the women go through after weight loss surgery.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.018
GPT teacher head0.249
Teacher spread0.232 · 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

Citations17
Published2012
Admission routes1
Has abstractyes

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