Bibliographic record
Abstract
OBJECTIVES: This article examines the extent of proxy reporting in the National Population Health Survey (NPHS). It also explores associations between proxy reporting status and the prevalence of selected health problems, and investigates the relationship between changes in proxy reporting status and two-year incidence of health problems. DATA SOURCE: Cross-sectional results are based on the 1996/97 NPHS Health file and General file. Longitudinal results are based on 1994/95 respondents who were still residing in households in 1996/97. ANALYTICAL TECHNIQUES: The extent of proxy reporting in the various NPHS files was computed. Prevalence estimates of selected health problems from the two 1996/97 cross-sectional files were compared. Multivariate analyses were used to estimate associations between proxy reporting status and health problems. MAIN RESULTS: For several health conditions, prevalence estimates based on the 1996/97 cross-sectional Health file (where proxy reporting was less common) were significantly higher than estimates derived from the General file. Individuals whose data were proxy-reported in 1994/95 and self-reported in 1996/97 had higher odds of reporting new cases of certain health conditions.
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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 | 0.028 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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".