<scp>David McKnight</scp>, <i>People, countries, and the Rainbow Serpent: Systems of classification among the Lardil of Mornington Island</i>. (Oxford studies in anthropological linguistics, 12.) Oxford & New York: Oxford University Press, 1999. Pp. x, 270. Hb $75.00.
Bibliographic record
Abstract
Anthropologists have long recognized that Australian aboriginal cultures have a rich repertoire of cognitive achievements, and they have contrasted this richness with the relative impoverishment of their technological repertoire. However, despite the richness of the cognitive repertoire, the anthropological literature contains no overall inventory for any aboriginal cultural group. McKnight's monograph is the first work that covers everything: social structure (including kinship), myth, ritual, dancing, property structure, and biological classification. The quality of the scholarship is very high. At the time of writing, McKnight had worked with the Lardil for 30 years, including 16 field trips, with a total time of residence among the Lardil of more than five years. After completing an MA on West African materials under Darryl Forde, he switched to Australia, where he also worked with the Wik-mungkan and a number of other groups. The present monograph is the first of a projected trilogy; work is under way now on the second volume, a monograph on marriage, sorcery, and violence. In recent years, McKnight has been involved, on behalf of the Lardil, in negotiations with the Australian government for land claims.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.050 | 0.021 |
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".