The origins of late nineteenth-century migrant diamond miners uncovered in a salvage excavation in Kimberley, South Africa
Bibliographic record
Abstract
The metric analysis of phenotypic variation observed in human skeletons is valuable for the determination of biological relatedness or ancestry, particularly when testing specific hypotheses concerning the possible ancestry of individuals from unmarked graves. The purpose of this paper is to determine the possible ancestry of unknown individuals excavated from an area next to the fenced Gladstone Cemetery in Kimberley, South Africa, using cranio-morphometry. The skeletons are thought to be those of migrant diamond mine labourers who died between 1897 and 1900. Two historical statements will be tested: firstly that black labourers came to work in Kimberley from various regions in Africa south of the equator and secondly that the local Khoe-San people did not participate in significant numbers as mine workers. Standard craniometric measurements were taken from 59 well-preserved male crania. These measurements were compared to craniometric data of eight modern and archaeological groups of males of known origin from Africa and Asia. Descriptive as well as univariate and multivariate statistical analyses were performed using SPSS. Eleven craniometric variables were selected for analysis. Results obtained are in accord with the historical documents stating that the majority of labourers at the Kimberley mines were migrant workers and that the local communities (including Khoe-San) did not contribute much to the workforce. Many of the labourers came from elsewhere in southern Africa (e.g. KwaZulu-Natal), but some may have originated from further afield. The heterogeneous nature of the sample reflects the varied origins of workers in Kimberley as well as some possible genetic admixture. This study reiterates the value of craniometric analyses as a tool to determine the probability of ancestry of unknown individuals when viewed in the light of contextual historical information.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".