Bibliographic record
Abstract
Ceramic technology was adopted by hunter-gatherers of the Paleo-Inuit Norton tradition in the Western Arctic between 2800 and 2500 years B.P., corresponding with an increase in the use of aquatic resources. Pottery production and use continued until approximately 1,500 BP, and resumed during the Neo-Inuit Birnirk and Thule periods, approximately 1,350 years BP. The technical characteristics of Norton and Thule ceramics suggest they performed differently when used for cooking, with Norton ceramics best suited for cooking using direct or suspended heat, and Thule ceramics best suited for indirect heat. Prior experimental archaeological research has focused on Thule ceramics, with limited investigation into the characteristics and performance of Norton ceramics. In this thesis, I asked how technological choices influenced the performance of ceramics for food processing, and how people in the Arctic cooked with ceramic vessels in the past. I addressed these questions through ceramics analysis and experimental archaeology. I analyzed a sample of Norton and Thule ceramics from occupation contexts from two Northern Alaskan sites, Iyatayet (NOB-0002) and Nukleet (NOB-0001), and compared the resulting data with existing ceramic data from other sites in Alaska to identify temporal and regional variation in ceramic characteristics. The results of this analysis provided metric data on which I based my experimental replications. For Phase 1 of my experimental research, I created and tested tiles with different temper types and surface treatments linked to ceramic cooking performance. For Phase 2, I replicated Norton and Thule vessels and used them to bring water to a boil using each of the three heating methods in order to answer questions of use by comparing heating performance of the two pottery traditions. My analysis of Norton and Thule ceramic assemblages revealed significant temporal and regional patterns in the shape and composition of vessels, particularly in temper type and decoration. Phase 1 of my experimental work identified differences in strength and porosity of test tiles with specific temper and surface treatment. The experimental heating trials showed that there are significant differences in performance, measured in minutes for water to reach a boil, between vessels used for the three heating methods, with indirect (stone boiling) heating being the most effective regardless of vessel tradition. The trials did not show significant differences between the performance of Norton compared to Thule vessels. This suggests that the distinctive characteristics of Norton and Thule pottery are not necessarily the result of specific choices made by
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".