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Record W2768436470 · doi:10.1177/1540415317744500

Do Hispanic Girls Develop Eating Disorders? A Critical Review of the Literature

2017· review· en· W2768436470 on OpenAlexafffund
Myanca Rodrigues

Bibliographic record

VenueHispanic Health Care International · 2017
Typereview
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsYork University
FundersHealth Innovation Network South LondonYork University
KeywordsBulimia nervosaAnorexia nervosaEating disordersEthnic groupBinge-eating disorderAcculturationPsychologyAffect (linguistics)Clinical psychologyBinge eatingPsychiatryMedicine

Abstract

fetched live from OpenAlex

INTRODUCTION: Eating disorders have become increasingly prevalent in North America. Anorexia nervosa, bulimia nervosa, and binge eating disorder were previously thought to solely affect Caucasian women. However, contemporary research has studied the occurrence of this phenomenon in ethnic minority women, such as Latinas. METHODS: This article presents a critical review of 12 quantitative, prospective psychological research studies from the past 17 years. RESULTS: The authors in the reviewed literature identified bodily dissatisfaction, environmental influences, and acculturation as significant risk factors in the development of eating disorders in Hispanic girls and women. CONCLUSION: The methodology and empirical findings from these studies are discussed, and suggestions for future research and culturally sensitive clinical treatment are considered.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.090
GPT teacher head0.474
Teacher spread0.384 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations11
Published2017
Admission routes2
Has abstractyes

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