Bibliographic record
Abstract
1. The Birth of Ciencias Antropologicas at the University of Buenos Aires, 1955-1965 (Rosana Guber and Sergio Visacovsky) 2. My Old Friend in a Dead-end of Empiricism and Skepticism: Bogoras, Boas, and the Politics of Soviet Anthropology of the late 1920s-early 1930s (Sergei Kan) 3. Taking Ethnological Training Outside the Classroom: The 1904 Louisiana Purchase Exposition as Field School (Nancy J. Parezo and Don D. Fowler) 4. Presentist History as a Means to Overturn Qualified Authority: A (False) Warrant for a New Archaeology in the 1960s and 1970s (R. Lee Lyman) 5. Pigs for Dance Songs: Reo Fortune's Empathetic Ethnography of the Arapesh Roads (Lise Dobrin and Ira Bashkow) 6. Diamond Jenness's Arctic Ethnography and the Potential for a Canadian Anthropology (Robert L. A. Hancock) 7. Reflections on Departmental Traditions and Social Cohesion in American Anthropology (Regna Darnell) 8. Anthropology, Theory and Research in Iroquois Studies, 1980-1990: Reflections from a Disability Studies Perspective (Gail Landsman) 9. A Swedish Ethnographer in Sulawesi: Walter Kaudern (Christer Lindberg) 10. Culture and Personality In Henry's Backyard: Boasian War Allegories in Children's Science Writ Large Stories (Elizabeth Stassinos)
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.130 | 0.034 |
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".