MétaCan
Menu
Back to cohort
Record W2976376601 · doi:10.7202/1064496ar

Call Me Angakkuq: Captain George Comer and the Inuit of Qatiktalik

2019· article· en· W2976376601 on OpenAlexvenueaboutno aff
Bernadette Driscoll Engelstad

Bibliographic record

VenueÉtudes/Inuit/Studies · 2019
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsGeorge (robot)ArcticArchaeologyWhite (mutation)AnthropologyPortraitHistoryEthnographyPoliticsArt historySociologyOceanographyLaw

Abstract

fetched live from OpenAlex

Through many years of dedicated fieldwork in the Canadian Arctic, Captain George Comer laid a solid foundation for the future of museum anthropology. With the support of Franz Boas, Captain Comer—a New England whaling master with little formal schooling—assembled an extensive collection of Inuit ethnographic and archaeological artifacts, photographs, sound recordings, and natural history specimens for the American Museum of Natural History in New York City, as well as major museums in Berlin, Ottawa, and Philadelphia. This article examines a remarkable segment of that collection, the production of Inuit facial casts—portraits of over two hundred men, women, and children—created by Comer at Qatiktalik (Cape Fullerton), a whaling site on the west coast of Hudson Bay. In tandem with photographs taken by Comer, Geraldine Moodie, and others at the time, these facial casts comprise a vital chapter of Inuit social history, preserving the memory of individuals and families who lived, worked, and traded at Qatiktalik. Accompanied by detailed biographical documentation prepared by Captain Comer, this extraordinary collection acknowledges the significance of personhood, a key concept in modern anthropological theory, and provides meaningful insight into the early social, cultural, and political history of Nunavut in the Canadian Arctic.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.384
Teacher spread0.331 · 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 designQualitative
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

Citations1
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueÉtudes/Inuit/StudiesSame topicIndigenous Studies and EcologyFrench-language works237,207