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Record W2119815862 · doi:10.1177/1049732314529667

Blame, Shame, and Lack of Support

2014· article· en· W2119815862 on OpenAlexafffund
Sara Kirk, Sheri Price, Tarra L. Penney, Laurene Rehman, Renée Lyons, Helena Piccinini‐Vallis, Michael Vallis, Janet Curran, Megan Aston

Bibliographic record

VenueQualitative Health Research · 2014
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsBridgepoint Active HealthcareIzaak Walton Killam Health CentreDalhousie University
FundersCanada Research ChairsNova Scotia Health Research Foundation
KeywordsBlameShameDiversity (politics)Qualitative researchPower (physics)PoliticsObesityHealth carePsychologySocial psychologySociologyMedicinePolitical scienceSocial science

Abstract

fetched live from OpenAlex

In this research, we examined the experiences of individuals living with obesity, the perceptions of health care providers, and the role of social, institutional, and political structures in the management of obesity. We used feminist poststructuralism as the guiding methodology because it questions everyday practices that many of us take for granted. We identified three key themes across the three participant groups: blame as a devastating relation of power, tensions in obesity management and prevention, and the prevailing medical management discourse. Our findings add to a growing body of literature that challenges a number of widely held assumptions about obesity within a health care system that is currently unsupportive of individuals living with obesity. Our identification of these three themes is an important finding in obesity management given the diversity of perspectives across the three groups and the tensions arising among them.

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)0.014
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.029
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.023
Scholarly communication0.0050.005
Open science0.0010.007
Research integrity0.0030.005
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 head0.813
GPT teacher head0.765
Teacher spread0.048 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations122
Published2014
Admission routes2
Has abstractyes

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