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Weight bias and identity characteristics among students at a public university in Southern Brazil

2024· article· en· W4402682259 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRevista de Nutrição · 2024
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsIdentity (music)Public universityPsychologyPolitical sciencePublic administrationPhysics

Abstract

fetched live from OpenAlex

ABSTRACT Objective Despite the consequences of weight discrimination for health inequities, its relationship with identity characteristics remains poorly understood. We investigated whether and to what extent discrimination attributed to body weight is linked to sociodemographic and identity factors. Methods This cross-sectional study is based on a representative sample of undergraduate students from the Federal University of Santa Catarina. Information on perceived discrimination was collected using the brief version of the Explicit Discrimination Scale. Socioeconomic and demographic data were also collected. Results: The results showed that 22.8% of the sample reported experiencing discrimination for being “fat or thin” throughout their lives. Perceived weight discrimination was higher among respondents whose household heads had completed up to high school education, and among those who were overweight and rated their health as “poor.” Conclusion Perceived weight discrimination was associated with significant factors linked to the stigmatization and pathologization of body weight. These findings should be considered in more inclusive approaches aimed at counteracting the embodiment of social inequalities.

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.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.070
GPT teacher head0.423
Teacher spread0.354 · 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