Analogues at Iqaluktuuq: The social context of archaeological inference in Nunavut, Arctic Canada
Bibliographic record
Abstract
This paper presents a case study from the Canadian Arctic, in which the community context of an archaeological project has led to a re-thinking of a fundamental aspect of archaeological interpretation. Archaeologists are constantly confronted with the problem of identifying appropriate analogues for the societies whose material remains they study. In the Arctic, a particularly rich ethnographic record exists relating to recent Inuit lifeways; however, it remains difficult to determine when, if ever, it should be used to interpret the Palaeo-Eskimo archaeological record which pre-dates 1,000 BP. This issue will be explored within the context of the Iqaluktuuq Project, a new program of field research which aims to combine the traditional knowledge of modern Inuit elders with the Palaeo- and Neo-Eskimo archaeological records in the Ekalluk River region of southeastern Victoria Island, Nunavut. Ultimately, the social engagement of archaeologists with elders has led to a reconsideration of the process of analogical inference, resulting in a more robust use of recent Inuit lifeways as models for Palaeo-Eskimos than would have occurred based on purely 'academic' considerations.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.029 | 0.010 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".