ARD volume 25 issue 2 Cover and Back matter
Bibliographic record
Abstract
His research focuses on issues of ethnographic analogy, archaeological interpretation, and the emergence of inequality.He has conducted ethnographic research in Mali, West Africa, and is currently directing an archaeological field programme on Casas Grandes sites in northern Mexico.Most recently, he has published an edited volume (with Robert M. Rosenswig) titled Modes of production and archaeology (2017).Alexandra Ion is an anthropologist and osteoarchaeologist interested in the ethics and history of body research and display.Her research focuses on the ways in which anthropologically and archaeologically derived categories have defined mortuary remains in academic scholarship, and the interdisciplinary study of European Neolithic human remains.Her current project explores the construction of the prehistoric body, by studying the post-mortem fate of human remains discovered in Neolithic settlements in the Balkan area, towards the reinterpretation of such deposits from a taphonomic perspective. Ben Jervis is Lecturer in Medieval Archaeology at the School of History, Archaeology and Religion
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.911 | 0.867 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".