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Record W1752982404 · doi:10.3138/topia.32.201

Eyewitness to a Whale Hunt: Theory, Event, and Apology in the Inuit North

2015· article· en· W1752982404 on OpenAlexvenueaboutno aff
David Laurence Dunne

Bibliographic record

VenueTOPIA Canadian Journal of Cultural Studies · 2015
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsWhalingWhaleHistorySovereigntyEthnologyLawArchaeologyPolitical science

Abstract

fetched live from OpenAlex

The paper revisits a whale hunt that took place in the vicinity of the hamlet of Pangnirtung, Nunavut, in 1998. An eyewitness to the hunt, I wrote a Master’s thesis, “The Bowhead Whale Hunt at Kekerten, Nunavut Territory (July 1998),” giving a chronicle of its duration and preparation. The hunt was undertaken by the Inuit as a way of dealing with a haunted piece of their past: the catastrophic aftermath of the presence of European whalers in the region in the 19th and early 20th centuries, which deeply challenged both the physical and cultural survival of the Inuit of the Eastern Arctic. The hunt was carried out at a significant site of memory/ lieu de mémoire: a former whaling station in proximity to the community. An important aspect of the Pangnirtung hunt was the assertion of Inuit collective identity in the claim of sovereignty over the management of bowhead whale stock in the months preceding the creation of Nunavut, in April 1999. Yet departing from conventional interpretations that would understand the Inuit as the recipients of a “gift” in a cycle of forgiveness and restitution (apology-as-discourse), I argue that the event itself was not the result, but the very substance of apology. Bringing the past forward into the present, the Inuit of Pangnirtung introduced an event as a critical requirement in undertaking the work of apology.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0140.031
Scholarly communication0.0110.010
Open science0.0030.008
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0070.001

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 head0.107
GPT teacher head0.412
Teacher spread0.305 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2015
Admission routes2
Has abstractyes

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Same venueTOPIA Canadian Journal of Cultural StudiesSame topicIndigenous Studies and EcologyFrench-language works237,207