Comparison of indicators of material circumstances in the context of an epidemiological study
Bibliographic record
Abstract
BACKGROUND: Since individual-level income is difficult to collect, investigators often rely on group-based measures derived from census data. No study has assessed the use of residential property values as an indicator of individual material circumstances. We aimed to compare two proxy indicators of material circumstances, one based on residential value and the other on median census tract income, to self-reported household income. METHODS: We used data from a case-control study (1996-2002), restricting analyses to 676 residents of the Island of Montreal for whom the three indicators were available. The degree of discrepancy between the residential value index, census income, and self-reported household income--each in 5 categories--was estimated, along with overall and weighted Kappas. RESULTS: When comparing residential value index and census income to self-reported household income, perfect concordance was observed for 38% and 30% of subjects, respectively; very good concordance, defined as ≤1 category difference, was observed for 76% and 69% of subjects, respectively. When compared to self-reported household income, overall and weighted Kappas showed stronger agreement with residential value index (weighted Kappa=0.37, 95% CI: 0.32, 0.42) than with census income (weighted Kappa=0.25, 95% CI: 0.20, 0.30). CONCLUSIONS: A residential value index may provide a measure of material circumstances that is closer to self-reported household income than the commonly used census income. Each indicator presents advantages and disadvantages, and their choice may depend on study objectives and feasibility.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.029 | 0.115 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".