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Record W4303415870 · doi:10.1017/s0008423922000749

Language Matters: The Study of Canadian Politics through an Exploration of Syllabi and Comprehensive Exams

2022· article· en· W4303415870 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCanadian Journal of Political Science · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Science Research and Education
Canadian institutionsUniversity of TorontoUniversité du Québec à MontréalUniversité de Sherbrooke
Fundersnot available
KeywordsSyllabusFrenchPoliticsRepresentation (politics)Reading (process)Field (mathematics)Political scienceSociologyLibrary scienceHumanitiesLawComputer science

Abstract

fetched live from OpenAlex

Abstract The representation of Canada's two main linguistic groups in the teaching of Canadian politics is crucial, but we know little about it. In this article, we analyze the systemic underrepresentation of francophone authors in Canadian political science by examining the research that students are exposed to. Based on data from 351 syllabi across 42 Canadian universities, as well as data from the reading list of the doctoral qualifying field exams in Canadian politics, our findings show that francophone authors are systemically underrepresented (when not totally absent). About 38 per cent of Canadian politics courses include no francophone authors in their reading lists. Our findings suggest that Canadian politics is not an inclusive and comprehensive field. This result entails important implications not only for current professors and students but also for the profession more generally, given that the students who will make up tomorrow's faculties in Canadian universities are shaped by these biases.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.003
Scholarly communication0.0000.001
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 head0.131
GPT teacher head0.403
Teacher spread0.272 · 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