Bibliographic record
Abstract
In pulling together these pithy citations from respected Americanist works, sometimes now called Indienology, this commentary attempts a comprehensive overview of notions relating to the person, in both cosmic and personal senses, of Native North America. It uses the European solution for distinguishing those indigenous to India from those of America by the expedient of a single vowel: a or e. Moreover, to clinch the argument, comparable Inuit data are included. This treatment is intended to be balanced, indicating features that both helped and harmed individuals and communities, using citations from scholars who convey statements in a Native voice upholding the interconnectedness of customs, taboos, demeanors, and their likely outcomes.\nThough reported as asides or seemingly obscure details for only a single tribe or instance, all these observations can be understood to have continent-wide distribution, providing a coherent worldview that was accepted, rejected, modified, or ignored depending on local conditions of terrain, history, customs, contacts, and inter-group hostilities. Local factors of population densities, social systems, and tending (foraging) or tilling (farming) lifeways are largely ignored here in the interest of tracing more generic patterns. Spatial orientations in worlds and homes are as significant as cultural rules since they provided the basic “staging area” for the active deployment of people and materials for larger tasks and activities.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".