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Record W4400823401 · doi:10.32920/jcd.v7i2.1983

Artful Compassion

2024· article· en· W4400823401 on OpenAlexaffvenue
Phillip Joy, Megan White, Megan Aston

Bibliographic record

VenueJournal of Critical Dietetics · 2024
Typearticle
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsDalhousie UniversityMount Saint Vincent University
Fundersnot available
KeywordsCompassionPsychologyPsychoanalysisArtPhilosophyTheology

Abstract

fetched live from OpenAlex

This research explores experiences of compassion in the eating disorder recovery processes of 2S/LGBTQ+ people. There exists a growing body of evidence suggesting disparities in the assessment, treatment, and overall care of eating disorders in 2S/LGBTQ+ communities. One concern is a potential lack of compassion, which can exacerbate feelings of isolation for 2S/LGBTQ+ individuals. To gain a deeper understanding of this issue, we embrace a queer poststructuralist approach to our research that disrupts traditional knowledge and acknowledges experiences as socially constructed. Semi-structured interviews with 14 self-identifying 2S/LGBTQ+ people who have experienced eating disorder care were conducted. Analysis of the data revealed three main types of experiences: 1) Experiences of otherness, 2) Experiences of compassion in eating disorder care, and 3) Experiences of compassion in queer communities. To “queer” our findings, we present them through graphic art and non-traditional scientific writing. The graphic art represents participants’ experiences and is followed by critical discussions that further explore the socially constructed nature of their experiences. Our findings underscore the critical need for enhanced compassion for 2S/LGBTQ+ people during treatment 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 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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.782
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.068
GPT teacher head0.429
Teacher spread0.361 · 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 teacher head, not a consensus.

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

Citations0
Published2024
Admission routes2
Has abstractyes

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