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Record W1993936361 · doi:10.3138/ijcs.2014.007

Please Pass the Crumpets … er, Croissants: Teaching Québec in Victoria, British Columbia

2014· article· en· W1993936361 on OpenAlexvenueaboutno aff
Marie Vautier

Bibliographic record

VenueInternational Journal of Canadian Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsIgnoranceSociologyColumbia universityGreenwichMedia studiesLibrary scienceHistoryPolitical scienceLaw

Abstract

fetched live from OpenAlex

In Sanctioned Ignorance (2013), based on his doctoral thesis in comparative literature (University of Alberta), Paul William Martin provides an overview of “the teaching of the literatures of Canada.” Framed by Pierre Bourdieu’s theories of “the market of symbolic goods” and based on fieldwork which consists of in-depth interviews with professors in French and English university departments and an examination of university calendars, his work offers a fascinating “snapshot” of the teaching of our literatures. Over several pages, Martin investigates and comments upon the unique program that I run at the University of Victoria: the undergraduate degree in comparative Canadian literature, jointly offered by the departments of English and French. This highly specialized undergraduate degree concentrates on classic literary texts from English-speaking Canada and French-speaking Québec (with subfields in Québec cinema and Québec history and various courses on culture and literature: Cartier and Champlain; graphic novels; Métis, migrant, and Amerindian writing; fine art; and so on). In this article, I propose the advantages of such a program to the future of the study of Québec in Canada, examine the challenges I have faced in maintaining this program over the past twenty-five years, and reflect on the teaching of the literature and culture of Québec in an anglophone university in the city that is identified as being “more British than the British”: Victoria, British Columbia.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.155
Threshold uncertainty score0.797

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.269
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.

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

Citations1
Published2014
Admission routes2
Has abstractyes

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