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Record W4403523162 · doi:10.21900/j.alise.2024.1627

Assessing Fatphobia in Public Library Programming: Is Wellness Size-Inclusive?

2024· article· en· W4403523162 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

VenueProceedings of the ALISE Annual Conference · 2024
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsWestern University
Fundersnot available
KeywordsComputer sciencePolitical science

Abstract

fetched live from OpenAlex

This content analysis of wellness-related library programs and programming materials seeks to discover the perception of larger bodies within library health programming. Fatphobia or sizeism is prevalent in the wellness industry and within healthcare. Libraries are trusted resources for health information. Informed by the fields of fat studies, we approached health programming in libraries by asking if larger people would feel welcome and able to attend. We examined twenty libraries’ programs over the past year as well as library conference programs and programming materials from several websites. There was little evidence of explicit sizeism, but some resources reproduced sizeist stereotypes and language. This presentation takes a fat pedagogy approach to focus on methods for ensuring access to all and expanding current definitions of inclusivity so that people with larger bodies recognize that libraries are welcoming spaces.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.006
Open science0.0010.001
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 head0.073
GPT teacher head0.421
Teacher spread0.348 · 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