Relationship between subjective social status and perceived health among Latin American immigrant women
Bibliographic record
Abstract
OBJECTIVE: to explore the relationship between socioeconomic status and subjective social status and explain how subjective social status predicts health in immigrant women. METHODS: cross-sectional study based on data from 371 Latin American women (16-65 years old) from a total of 7,056 registered immigrants accessed through community partners between 2009-2010. Socioeconomic status was measured through education, income and occupation; subjective social status was measured using the MacArthur Scale, and perceived health, using a Likert scale. RESULTS: a weak correlation between socioeconomic and subjective social status was found. In the bivariate analysis, a significantly higher prevalence of negative perceived health in women with no education, low income, undocumented employment was observed. In the multivariate analysis, higher odds of prevalence of negative perceptions of health in the lower levels of the MacArthur scale were observed. No significant differences with the rest of the variables were found. CONCLUSIONS: the study suggests that subjective social status was a better predictor of health status than the socioeconomic status measurements. Therefore, the use of this measurement may be relevant to the study of health inequalities, particularly in socially disadvantaged groups such as immigrants.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".