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Record W4388112443 · doi:10.1080/09581596.2023.2273201

How pharmaceutical companies misappropriate fat acceptance

2023· article· en· W4388112443 on OpenAlexaff
Andrea E. Bombak

Bibliographic record

VenueCritical Public Health · 2023
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsStigma (botany)Pharmaceutical industryPublic relationsHealth professionalsIntervention (counseling)Pharmaceutical careHealth careBusinessMarketingPsychologyMedicineNursingPolitical sciencePharmacyPsychiatryPharmacologyLaw

Abstract

fetched live from OpenAlex

Pharmaceutical companies influence whether we perceive conditions as relevant to the medical sector and in need of pharmaceutical intervention (pharmaceuticalization). Recently, through coordinated media and professional campaigns, pharmaceutical companies are coming to influence our understanding of bodily size. Beyond merely affecting conversations about how weight should be understood and engaged with in healthcare, however, pharmaceutical companies are swaying how society approaches weight stigma. By elevating certain voices, those of organizations and clinicians with whom they partner, and not others, including fat acceptance activists, pharmaceutical companies are having a regressive impact on body acceptance veiled as “obesity” stigma advocacy.

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)0.033
metaresearch head score (Gemma)0.084
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.084
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0120.021
Scholarly communication0.0160.009
Open science0.0010.008
Research integrity0.0100.013
Insufficient payload (model declined to judge)0.0090.002

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 head0.378
GPT teacher head0.562
Teacher spread0.184 · 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 designQualitative
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

Citations9
Published2023
Admission routes1
Has abstractyes

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