IS THE HEALTH OF OLDER AMERICANS WITH A GED EQUIVALENT TO THEIR PEERS WITH A HIGH SCHOOL DIPLOMA?
Bibliographic record
Abstract
Abstract Previous research has found higher levels of educational attainment to be strongly associated with better health outcomes in later life, such as better cognitive functioning and fewer functional and sensory impairments. However, most studies have grouped General Educational Development (GED) recipients with high school graduates, neglecting potential differences in socioeconomic status, health behaviours, and health outcomes among these two groups. The aim of the current study is to identify differences in the age-sex-race-poverty adjusted prevalence and odds of cognitive impairment, hearing impairment, vision impairment, limitations in activities of daily living (ADLs), and ambulation limitations among three groups of older American adults: high school dropouts, GED recipients, and high school graduates with no post-secondary education. The present study uses secondary analysis of the 2017 American Community Survey, a nationally representative survey of community-dwelling and institutionalized older adults aged 65 years and older, of whom 20,489 were GED recipients, 154,892 had a high school diploma and 49,912 had finished grade 8 but had not completed high school. Our findings indicate that there is a gradient in health outcomes among Americans aged 65-84, with the highest prevalence and odds of cognitive impairment, hearing impairment, vision impairment, ADL limitations, and ambulation limitations occurring among high school dropouts, followed by GED recipients, and the lowest prevalence among high school graduates. These findings suggestion that although GED recipients have better health outcomes than high school dropouts, there is still a significant disparity in health status between GED recipients and high school graduates.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".