Bibliographic record
Abstract
Maine archaeologists continue to learn more about the pre-European past, often changing once accepted ideas. Among these is the nature of the so-called “Red Paint Peoplewho were not a distinct race or people, but various Native Americans groups who happened to bury their dead with red ocher between 6000 and 2000 B.C. Another popular idea is the erroneous notion that early Maine Native peoples migrated from coast to interior on a seasonal basis. Recent research questions this belief and explores the reasons for its persistence. Finally, the paper discusses the problem of extending modern political-ethnic terms, such as Penobscot Nation, back into pre-European times. Professor David Sanger has researched the pre-European period in Maine and the Maritime Provinces since 1966 when he joined the Canadian Museum of Civilization in Ottawa upon completing his Ph.D. in Anthropology at the University of Washington. He joined the faculties of the Department of Anthropology and the Institute for Quaternary Studies at the University of Maine in 1971. Emphasizing the relationship between culture and environment, he has published extensively on the archaeology of the region and the ever-changing environments to which the Native peoples had to adapt.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.053 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".