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Record W4409880511 · doi:10.3138/jcs-2023-0057

Schoolteachers, Technologies of the Self, and the Genealogy of the Late Modern Subject: The <i>Bulletin</i> of the Queen’s Summer School Association, 1915–1932

2025· article· en· W4409880511 on OpenAlexaffvenueabout
Scott McLean, Erin Knox

Bibliographic record

VenueJournal of Canadian Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical Education Studies Worldwide
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsQueen (butterfly)Subject (documents)Association (psychology)GenealogyHistoryDemographySociologyLibrary sciencePsychologyComputer science

Abstract

fetched live from OpenAlex

From the 1920s through the 1960s, thousands of Canadian schoolteachers spent much of their summer holiday period attending courses organized by universities or provincial departments of education. In the 1920s, Queen’s University attracted students from every Canadian province to attend summer school in Kingston, Ontario. Through a content analysis of one hundred messages written by schoolteachers from across Canada, this article analyzes a technology of the self deployed in an effort to encourage other schoolteachers to enrol at Queen’s University. The authors of these messages divided schoolteachers into two camps: those who were progressive, industrious, and ambitious and others. They positioned themselves and their readers as subjects with the responsibility of choosing the camp to which they belonged. This article decentres the study of power in the history of teacher education by analyzing how schoolteachers themselves governed schoolteachers. It demonstrates that technologies of the self are linked to the material interests of those who deploy them. The article furthers the genealogical study of late modern subjectivities by demonstrating that technologies of the self, which position human subjects as reflexive and autonomous beings responsible for shaping their own lives through conscious choices, were highly developed in the early twentieth century in Canada.

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)0.003
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
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 score0.745
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.275
Teacher spread0.260 · 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.

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
Published2025
Admission routes3
Has abstractyes

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