Bibliographic record
Abstract
absolutism 7-8 accountability 16, 17-18 Acoma Pueblo 32 Acoose, Janice 274 adaawx 188, 192-3 ADR see Alternative Dispute Resolution (ADR) practices advertising and archaeological symbols 20-1 aesthetic interests 22-3 Ahayuda (Zuni tradition) 33 Alexie, Robert 271 Alexie, Sherman 95, 273 Alper, J.S. and Beckwith, J. 128 Alternative Dispute Resolution (ADR) practices 39-40 Anasazi sites 24 Ancient Burial Grounds Act 1974.(Prince Edward Island) 58-9 'Angle of Repose' (Stegner) 275 'Annishnaabe Scout' (Hamilton MacCarthy) 215, 222 appetite-suppressing plant remedies see Hoodia plants appropriation defi nitions 2-3 see also cultural appropriation Arbour, L. and Cook, D. 135 archaeological practice codes of conduct 16 contemporary challenges 16-17 goals and mandates, historical contexts 14-19 permissions and control of access 27-8 archaeological research 26-7 challenges to 16-17 see also genetic research; scientifi c research Archibald, J-A.et al. 6 archives and power 204 see also museums Ardouin, Claude 258 Aristotle 77 Arizona State University 133-4 art concepts 246 and cross-cultural respect 250, 254 art museums 238-9, 244-7 objections and responses to artifact display 248-54 and trans-cultural understandings 250 'artifacts' acquisition histories 226-7, 253-4 decontextualization issues 246-7, 251-3 defi ned 235 artistic representations see subject appropriation
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.659 | 0.438 |
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".