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Que(e)rying the Canadian North : Agnes Deans Cameron’s Journey from Imperial Empowerment to the Margins of Memory

2021· dissertation· W7151010888 on OpenAlexaboutno aff
Laurence Georgin

Bibliographic record

Venuenot available
Typedissertation
Language
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsnot available
Fundersnot available
KeywordsEthnographyContext (archaeology)Perspective (graphical)

Abstract

fetched live from OpenAlex

Interroger et remettre en question le nord canadien : le voyage d’Agnes Deans Cameron de l’empouvoirement impérial aux marges de la mémoire Pourquoi n'y a-t-il rien plutôt que quelque chose? Interroger et remettre en question le nord canadien: Le voyage d’Agnes Deans Cameron de l’empouvoirement impérial aux marges de la mémoire vise à déterminer pourquoi l'enseignante, la journaliste et l’écrivaine de voyage canadienne du début du vingtième siècle, Agnes Deans Cameron, a pratiquement été oubliée et rarement évoquée jusqu'à très récemment, malgré l’incroyable voyage qui la conduisit en 1908 vers la mer de Beaufort et le succès de son livre, The New North: Being Some Account of a Woman's Journey through Canada to the Arctic, et en dépit d’une renommée, qui s'étendait du Canada aux États-Unis et au Royaume-Uni. Pour répondre à cette question, nous explorerons le contexte historique, social et culturel dans lequel elle a voyagé dans le Nord canadien, notamment en ce qui concerne la place des femmes dans l'histoire du voyage et l'écriture du voyage. Cette thèse interroge ce que ses écrits et sa personnalité publique peuvent nous dire d’un monde en mutation au tournant du vingtième siècle: quel était son message, comment il a été promu et reçu, quelle contribution a-t-il apporté au débat colonial, et pourquoi est-il toujours pertinent aujourd'hui quand on observe comment ce passé est analysé et rapporté aux lecteurs contemporains, et comment la mémoire collective est façonnée et créée à travers ces procédés?

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)0.003
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.065
Threshold uncertainty score0.413

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0440.037
Scholarly communication0.0120.006
Open science0.0010.005
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0120.001

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 head0.016
GPT teacher head0.230
Teacher spread0.214 · 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
Published2021
Admission routes1
Has abstractyes

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