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Record W7042855756

Qallunology of an Arctic Whaling Encounter: An Inuk’s Transatlantic Voyage, 1839 to 1840

2022· dissertation· en· W7042855756 on OpenAlexaboutno aff

Bibliographic record

VenueUVic’s Research and Learning Repository (University of Victoria) · 2022
Typedissertation
Languageen
FieldBusiness, Management and Accounting
TopicE-commerce and Technology Innovations
Canadian institutionsnot available
Fundersnot available
KeywordsWhalingIndigenousArcticSubsistence agricultureScotsThe arctic
DOInot available

Abstract

fetched live from OpenAlex

This thesis borrows the analytical framework of Qallunology to examine a nineteenth-century Arctic whaling encounter between Scottish whalers and an Inuk geographer: Inulluapik. This thesis analyzes the narrative, written by Scottish surgeon Alexander M’Donald, of Inulluapik’s transatlantic journey to Aberdeen, Scotland and Tinnujivik (Cumberland Sound) from 1839 to 1840. I show how Inulluapik’s experience in Aberdeen in 1839, as recorded by M’Donald, provides insight into early Victorian worldviews and perceptions, which I call M’Donald’s Qallunaat-dom and Qallunaat-ness. By conducting a Qallunology of M’Donald’s description of the historical episode, I examine his early Victorian Qallunaat-dom, which compared Inuit from the eastern Arctic to Scots in Aberdeen through his binary understanding of whaling, gender, and spirituality. M’Donald’s interpretation of Inulluapik’s experience demonstrated his contrasting views of Inuit and non-Inuit cultures, which intersected with early Victorian ideas of civilization, intelligence, behaviour, appearance, respectability, female domesticity and marital purity, and Indigenous authenticity. In contrast, Inulluapik demonstrated fluid resistance to M’Donald’s early Victorian binaries of subsistence versus commercial whaling, rural versus urban, primitive versus advanced, and uncivilized versus civilized, and Indigenous versus non-Indigenous.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.023
GPT teacher head0.278
Teacher spread0.255 · 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

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