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Record W2067756665 · doi:10.1037/1099-9809.10.1.81

Patterns of Pain Descriptor Usage in African Americans and European Americans With Chronic Pain.

2004· article· en· W2067756665 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCultural Diversity & Ethnic Minority Psychology · 2004
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupMcGill Pain QuestionnaireVisual analogue scaleExploratory factor analysisChronic painAfrican americanPsychologyAsian americansMexican americansFactor (programming language)Physical therapyPsychometricsClinical psychologyMedicinePsychiatryAnthropologyEthnologyHistory

Abstract

fetched live from OpenAlex

This study examined ethnic differences in the use of pain descriptors, comparing standardized pain assessment data from African American and European American patients with heterogeneous chronic pain syndromes. The measure was the Short-Form McGill Pain Questionnaire (SF-MPQ) including the embedded Visual Analog Scale (VAS). Exploratory factor analyses of SF-MPQ data identified differences in factor structure with the VAS loading on a different factor for each group. A 5-factor solution was obtained from the African American group and a 4-factor solution was obtained from the European American group. There was little overlap in the pattern matrices for African American and European American groups. Results suggest that the VAS is as sensitive to ethnic differences as other traditional pain measures.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.312
Teacher spread0.267 · 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