The Hamann‐Todd Human Osteological Collection: A Representative Sample?
Bibliographic record
Abstract
OBJECTIVES: The Hamann-Todd Human Osteological Collection (HTHOC) is a documented skeletal collection that has been foundational to the fields of biological anthropology and forensic anthropology. In constructing these standards, the HTHOC has been used as though it encapsulates the range of biological variation of humanity in North America. The powerful role that structural and cultural violence played in the creation of the HTHOC suggests that these individuals are not representative of broader Cleveland, let alone North America. Our goal is to assess several of the biases in the HTHOC. We compare the causes of death and the month of death of those in the HTHOC to the broader Cleveland population to assess whether the HTHOC is truly a representative sample. MATERIALS AND METHODS: We analyze the causes of death and months of death for individuals in the HTHOC (obtained from W. Montague Cobb's 1932 dissertation) to the contemporaneous Cleveland population (obtained from Mortality Statistics Annual Reports 1911-1930). RESULTS: We find notable differences in the causes of death between the HTHOC sample and Cleveland population, particularly in the percentage of deaths from tuberculosis. We also find statistically significant differences in the monthly distribution of deaths in the HTHOC compared to Cleveland. DISCUSSION: These discrepancies reflect structural inequalities surrounding how the HTHOC individuals were acquired and practical considerations in cadaver acquisition at Western Reserve Medical School. We intend for these findings to inform future decisions as communities and scholars grapple with moving forward with these types of skeletal collections.
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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 | 0.014 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".