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Record W2992183507 · doi:10.3148/cjdpr-2019-034

Weight Inclusive Practice: Shifting the Focus from Weight to Social Justice

2019· article· en· W2992183507 on OpenAlexaffvenueabout
Meredith Bessey, Daphne Lordly

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2019
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsMount Saint Vincent University
Fundersnot available
KeywordsMainstreamStigma (botany)OverweightWeight stigmaHealth careWeight managementPsychologySocial stigmaPopulationPublic relationsNursingObesityGerontologyMedicinePolitical scienceFamily medicineEnvironmental healthPsychiatryHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

Obesity is framed by mainstream media and health care professionals as an "epidemic" contributing to the ill health of the population. This paper reviews literature related to dominant discourses about weight in dietetics, drawing on literature from other health care disciplines, and how these discourses influence patient care. Emerging, competing discourses are also reviewed. Literature highlighted that dietitians and dietetic students are often biased and hold stigmatizing beliefs toward "overweight" and "obese" patients. No research has been conducted in Canada addressing this question, leaving this as an opportunity for future research. Weight stigma and interventions focused on weight have multiple negative implications for individuals, especially those living in larger bodies, including reluctance to seek health care, poor body image, subsequent weight gain, and increased disordered eating. There are alternative discourses emerging, which shift the focus away from weight and toward social justice. The ways in which dietetic students are trained to "manage" weight, and how dominant discourses influence this training, is an important area of future exploration. Dietetic professionals are encouraged to reflect on their weight biases and educate themselves on weight inclusive approaches to health, such as Health at Every Size and Well Now.

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)0.016
metaresearch head score (Gemma)0.032
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.811
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0020.002

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 head0.092
GPT teacher head0.509
Teacher spread0.417 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations12
Published2019
Admission routes3
Has abstractyes

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