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Record W3031074540 · doi:10.1186/s40337-020-00306-3

COVID19, the pandemic which may exemplify a need for harm-reduction approaches to eating disorders: a reflection from a person living with an eating disorder

2020· article· en· W3031074540 on OpenAlexaff
Margaret Janse van Rensburg

Bibliographic record

VenueJournal of Eating Disorders · 2020
Typearticle
Languageen
FieldPsychology
TopicEating Disorders and Behaviors
Canadian institutionsCarleton University
Fundersnot available
KeywordsPandemicEating disordersReflection (computer programming)HarmCoronavirus disease 2019 (COVID-19)Harm reductionReduction (mathematics)PsychologyPsychiatryMedicineSocial psychologyNursingComputer sciencePathologyPublic healthDisease

Abstract

fetched live from OpenAlex

This reflective piece, written by a woman with an eating disorder aims to identify the impact of COVID-19 on persons living with eating disorders and provide a social justice approach as a resolution. The author identifies that eating disorder behaviors may be the only coping tool available for many persons with eating disorders during this time of uncertainty. While she acknowledges the risks associated with eating disorder behaviors, she identifies that this time of uncertainty may be a time to embrace harm-reduction in approaching the health and wellness of persons with eating disorders.

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)0.006
metaresearch head score (Gemma)0.020
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.019
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0190.016
Scholarly communication0.0070.007
Open science0.0020.010
Research integrity0.0130.033
Insufficient payload (model declined to judge)0.0020.001

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 head0.123
GPT teacher head0.337
Teacher spread0.214 · 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
GenreCommentary

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
Published2020
Admission routes1
Has abstractyes

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