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Record W2155015170 · doi:10.1177/10791102009002005

Measuring Socioeconomic Status

2002· article· en· W2155015170 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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAssessment · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsSocioeconomic statusInter-rater reliabilityPsychologyScale (ratio)Rating scaleClinical psychologyDevelopmental psychologyDemographyGeographyPopulationSociologyCartography

Abstract

fetched live from OpenAlex

This study investigated issues related to commonly used socioeconomic status (SES) measures in 140 participants from three cities (Atlanta, Boston, and Toronto) in two countries (United States and Canada). Measures of SES were two from the United States (four-factor Hollingshead scale, Nakao and Treas scale) and one from Canada (Blishen, Carroll, and Moore scale). Reliability was examined both within (interrater agreement) and across (intermeasure agreement) measures. Interrater reliability and classification agreement was high for the total sample (ranger = .86 to .91), as were intermeasure correlations and classification agreement (range r = .81 to .88). The weakest agreement across measures was found when families had one wage earner who was female. Validity data for these SES measures with academic and intellectual measures also were obtained. Some support for a simplified approach to measuring SES was found. Implications of these findings for the use of SES in social and behavioral science research are discussed.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.659
Threshold uncertainty score0.997

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.094
GPT teacher head0.376
Teacher spread0.283 · 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