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
OBJECTIVES: There is uncertainty about whether position in a socioeconomic hierarchy confers different mortality risks on men and women. The objective of this study was to conduct a systematic review of gender differences in socioeconomic inequality in risk of death. METHODS: This research systematically reviewed observational cohort studies describing all cause or cause specific mortality for populations aged 25-64 in developed countries. For inclusion in the review, mortality had to be reported stratified by gender and by one or more measures of socioeconomic status. For all eligible studies, five absolute and six relative measures of the socioeconomic inequality in mortality were computed for male and female populations separately. RESULTS: A total of 136 published papers were reviewed for eligibility, with 58 studies deemed eligible for inclusion. Of these eligible studies, 20 papers published data that permitted the computation of both absolute and relative measures of inequality. Absolute measures of socioeconomic mortality inequality for men and women generally agreed, with about 90% of studies indicating that male mortality was more unequal than female mortality across socioeconomic groups. In contrast, the pattern of relative inequality results across the 20 studies suggested that male and female socioeconomic inequality in mortality was equivalent. CONCLUSIONS: Inferences about gender differences in socioeconomic inequality in mortality are sensitive to the choice of inequality measure. Wider understanding of this methodological issue would improve the clarity of the reporting and synthesis of evidence on the magnitude of health inequalities in populations.
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 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 | 0.101 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.006 |
| 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