to the source. Becoming Oldest-Old: Evidence from Historical U.S. Data
Bibliographic record
Abstract
We argue that the environment determines life span, using historical data to show that such indicators of environmental insults in early childhood and young adulthood as quarter of birth, residence, occupation, wealth, and the incidence of specific infectious diseases affected older age mortality. Consistent with improvements in early life factors, we find that the effect of quarter of birth on older age mortality has diminished over the twentieth century and that the declining impact of quarter of birth explains 16 to 17 percent of the difference in ten year mortality rates of Americans age 60-79 in 1900 and in 1960-1980. We estimate that at least one-fifth of the increase between 1900 and 1999 in the probability of a 65 year old surviving to age 85 may be attributable to early life conditions. We also present suggestive evidence on the mortality trajectory of the oldest
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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 | 0.000 | 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 | 0.001 | 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 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".