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Record W6963348136 · doi:10.20381/ruor-25399

Qamani’tuac

2018· article· en· W6963348136 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Ottawa - Library · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsOfficerCoast guardGovernment (linguistics)Guard (computer science)Order (exchange)

Abstract

fetched live from OpenAlex

The author is retired. In the 1970s, he was a navigating officer on Canadian Coast Guard ships. He revisited student life for his own interests and has seven postsecondary diplomas. He is presently registered in the Masters of World Literatures and Cultures. This article is adapted from a paper submitted for LCM5302 Travel and [literary] Theory, in October 2017. In Inuit culture and history, the town of Baker Lake should not exist. It was a seasonal camp where Inuit from different groups would gather, in summer, for hunting and fishing, with the goal of replenishing the supplies of their individual communities. The interference from European colonizers and the Canadian government has contributed to the artificial creation of Baker Lake. Was it an attempt to build Utopia? The author mixes his own travel memories (1973) with his literature research, in order to describe this mystery.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.951
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.001
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2770.068

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 head0.009
GPT teacher head0.150
Teacher spread0.141 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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