Younger Achievement Age Predicts Shorter Life for Governors: Testing the Precocity-Longevity Hypothesis With Artifact Controls
Bibliographic record
Abstract
McCann's precocity-longevity hypothesis suggests that the prerequisites, concomitants, and consequences of early peaks in career achievement may foster the conditions for premature death. In the present test of the precocity-longevity hypothesis, it was predicted that state governors elected at younger ages live shorter lives. Two competing explanatory frameworks, the life expectancy artifact and the selection bias artifact, also were tested. In a sample of 1,672 male governors, the precocity-longevity prediction was supported, and it was demonstrated with correlation, regression, and subsample construction strategies that the life expectancy and selection bias artifacts were not sufficient to account or the significant positive correlation between election age and death age. The positive correlation also was maintained when year of birth, years of service, span of service, and state of election were statistically controlled.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".