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Record W4400278918 · doi:10.3138/jcs-2023-0008

Cultural Distinction and the University of Toronto: Constructing Symbolic Boundaries of Social Class in Canada, 1894–1950

2024· article· en· W4400278918 on OpenAlexaffvenueabout
Scott McLean

Bibliographic record

VenueJournal of Canadian Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSocial and Cultural Dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSociologySocial classClass (philosophy)The SymbolicAnthropologySocial scienceMedia studiesEpistemologyPolitical sciencePsychologyLawPsychoanalysis

Abstract

fetched live from OpenAlex

In the first half of the twentieth century, the University of Toronto was a preeminent cultural institution in Canada. Based on a critical interpretation of archival documents, this article narrates the history of four non-formal educational programs through which the University of Toronto created opportunities for Canadians to develop privileged forms of cultural taste and practice: the administration of local examinations in music across Canada, the development of a museum oriented to public visitation, the organization of public lectures in collaboration with local associations across Ontario, and the delivery of non-credit evening courses in Toronto. These four programs engaged hundreds of thousands of Canadians in forms of activity that supported the development of what Bourdieu conceptualized as constellations of cultural distinction: arrays of tastes and practices that mark symbolic boundaries of social class. Two of the programs resulted in national cultural institutions (Royal Conservatory of Music and Royal Ontario Museum) prominent in fields that have been empirically associated with social class boundaries in Canada. The other two programs declined in significance after 1950 and have not previously been included in analyses of cultural distinction. This article explores the historical role of Canadian universities in constructing symbolic boundaries of social class.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.325
Threshold uncertainty score0.458

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.260
Teacher spread0.244 · 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 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

Citations2
Published2024
Admission routes3
Has abstractyes

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