Fluctuations in a Dreadful Childhood: Synthetic Longitudinal Height Data, Relative Prices and Weather in the Short-Term Health of American Slaves
Bibliographic record
Abstract
For over a quarter century anthropometric historians have struggled to identify and measure the numerous factors that affect adult stature, which depends upon diet, disease and physical activity from conception to maturity. I simplify this complex problem by assessing nutritional status in a particular year using synthetic longitudinal data created from measurements of children born in the same year but measured at adjacent ages, which are abundantly available from 28,000 slave manifests housed at the National Archives. I link this evidence with annual measures of economic conditions and new measures of the disease environment to test hypotheses of slave owner behavior. Height-by-age profiles furnish clear evidence that owners substantially managed slave health. The short-term evidence shows that weather affected growth via exposure to pathogens and that owners modified net nutrition in response to sustained price signals.
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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 | 0.003 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".