MétaCan
Menu
Back to cohort
Record W7125425607 · doi:10.48512/xcv8501882

Echoes of the Tuniit: Exploring Dorset-Inuit Interaction in Northern Nunatsiavut (WGF - Post-PhD Research Grant)

2022· article· en· W7125425607 on OpenAlexaboutno aff
Patrick C. Jolicoeur

Bibliographic record

VenueThe Digital Archeological Record (tDAR) · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsArcticIndigenousChronologyPopulationThe arcticResource (disambiguation)

Abstract

fetched live from OpenAlex

This resource is an application for a Post-PhD Research Grant from the Wenner-Gren Foundation. Inuit migration from Alaska to the Eastern Arctic (i.e. Canada and Greenland) around the 13th century AD is considered one of the most dramatic human population movements in North America. Around this same time, an existing Indigenous Arctic population, known as the Dorset culture by archaeologists, disappeared entirely. A major debate regarding these processes concerns the dynamics of Dorset-Inuit interaction. It is possible that the Dorset are the Tuniit of Inuit oral histories. While there is scant material evidence of exchange between the two peoples, there is evidence of chronological overlap in some regions of the Arctic. However, some regions, such as Nunatsiavut (Labrador Inuit lands), do not have sufficiently robust chronological data to understand if the Dorset became a part of Inuit social memory through direct face-to-face interaction or Inuit encountering long-abandoned Dorset archaeological remains. This project will address Dorset-Inuit interaction in Nunatsiavut by excavating two houses at Staffe Island 1, one of the earliest known Inuit sites in the region. By applying Bayesian modelling to refine the chronology at Staffe Island, this project will assess whether the two groups coexisted in the same region and debate how past human interactions can become part of long-lasting social memories.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.315
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.254
GPT teacher head0.409
Teacher spread0.155 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueThe Digital Archeological Record (tDAR)Same topicIndigenous Studies and EcologyFrench-language works237,207