A multicontextual approach to zooarchaeology: procurement strategies in the Mackenzie Delta Region, Western Canadian Arctic
Bibliographic record
Abstract
Large, complex, databases cannot be adequately comprehended with narrow methodologies and polarized theoretical frameworks. In an attempt to overcome these difficulties, this study develops a systematic multicontextual technique for the analysis of multiple archaeofaunal assemblages. The approach advocated here takes part in an emerging disciplinary trend that supports greater integration of archaeofaunas with multiple archaeological databases and diverse theoretical frameworks. This methodology is composed of two levels; (1) pattern recognition, and (2) evaluation against multiple interpretative contexts, or contexts of reference. A rigorous approach to pattern recognition was achieved through the complementary use of two multivariate statistical techniques; correspondence analysis and cluster analysis. These techniques allowed for the ordering of the faunal assemblages into five distinct Procurement Clusters, such that they could be compared against a number of models derived from multiple contexts of reference. This research framework is illustrated through analysis of a high resolution Neoeskimo faunal database from the Mackenzie Delta Region, western Canadian Arctic. The analysis suggests that a wide array of procurement adaptations were adopted by Neoeskimo groups in the region. In particular, at winter house sites, five specialized, or focal, economies were identified that appear to have been practiced simultaneously by different groups. This diverse economy is largely a result of a condensed array of productive ecological nodes in the Mackenzie Delta Region, which each attracted a unique constellation of migratory faunal resources. Nevertheless, the distribution of these nodes was not the only factor which mediated this pattern, and the development of these focal strategies also appears to have been in part associated with a suite of climatic, technological, demographic, and social changes that occurred throughout the period ca. 1200--1850 AD.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.011 | 0.018 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".