Bibliographic record
Abstract
Rogers’ (1999, 2009) visual method is a technique for estimating skeletal sex based on four traits of the distal humerus, and is valuable in cases of commingled or fragmented remains when use of more dominant cranial and pelvic methods is not possible. However, Rogers’ initial accuracy of 92% has not been replicated by subsequent tests of the method, and the role of biological ancestry in the accuracy of this method has not been sufficiently addressed. I conducted a blind test of the method on a sample of nineteenth-century American black and white individuals from the Hamann-Todd Collection. This test resulted in an overall accuracy of 67%, ranging from 54–73% between the two groups. These results demonstrate that accurate estimation of sex using the method is two times more likely for a white individual than for an black individual. More research is required to understand the cause of this variation. Prior to applying this method in bioarchaeological and forensic contexts, future should consider these results that the method is not consistently accurate across all human populations. Discipline: Anthropology (Honours) Faculty Mentor: Dr. Hugh McKenzie
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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 | 0.065 | 0.251 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".