A Multiple-Process Latent Transition Model of Poverty and Health
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.
Bibliographic record
Abstract
Health researchers often use the life-course perspective, exploring how long-range experiences in one life domain may influence, and be influenced by, those in another. We develop a multiple-process latent transition model (MPLTM) to estimate changes in health and poverty dynamics simultaneously, using repeated measures of self-rated health and income for working-aged adults from the British Household Panel Survey. We apply the model to quantify concurrent and longitudinal effects to assess whether changes in these two processes are related or independent. Model extensions add time-invariant (cohort, gender) and time-varying (weeks nonemployed in previous year) covariates. We find both concurrent and bidirectional longitudinal relationships between poverty and health, with nonemployment appearing to mediate longitudinal health-to-poverty effects and confound longitudinal poverty-to-health effects. The MPLTM can provide quantitative estimates of complex interlocking processes that are often difficult to measure and assess.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it