Bibliographic record
Abstract
A more robust archaeological interpretation can be produced if a multiscalar approach is brought to bear on the study of the past. In Iroquoian Archaeology and Analytic Scale, ten contributors conducting studies of groups around New York State and southern Ontario present contemporary research focused not only on examining the role of scale and how it impacts the field of Iroquoian studies, but also how archaeologists studying other Native Americans can expand their own research. Specifically, the contributors employ a variety of spatial, temporal, and methodological scales to reveal patterns and insights into the cultural interactions that might otherwise be missed by a less multiscalar approach. Furthermore, the diversity of research spans nearly a millennium, from AD 900 to 1800, and encompasses several different topographical settings, including major river flood-plains, upland headwater areas, and terraces along smaller tributaries, yielding a plethora of current findings from the largest of villages to the smallest of seasonal campsites. Laurie E. Miroff and Timothy D. Knapp have organized these essays in roughly chronological fashion and provide an introduction that addresses the importance of a multiscalar analysis. This volume of Iroquoian-specific yet wide-ranging essays will be of interest to anyone specializing in Native American studies in the Northeast. It will also benefit archaeologists who wish to gain a better understanding of how using a multiscalar approach in their own research can be an integral step toward a more dynamic view of the Native American lived experience.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".