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Record W2532866235 · doi:10.1080/00085006.2016.1239858

Watson Kirkconnell on “The place of Slavic studies in Canada”: a 1957 speech to the Canadian Association of Slavists

2016· article· en· W2532866235 on OpenAlexafffundvenueabout
Heather J. Coleman

Bibliographic record

VenueCanadian Slavonic Papers · 2016
Typearticle
Languageen
FieldArts and Humanities
TopicTranslation Studies and Practices
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsSlavic languagesWatsonSlavic studiesMulticulturalismCommunismCivilizationHistoryPolitical scienceClassicsLawPolitics

Abstract

fetched live from OpenAlex

This article introduces and reprints a speech by Watson Kirkconnell to the Canadian Association of Slavists in 1957. Watson Kirkconnell (1895—1977) was an influential Canadian scholar, university administrator, Baptist activist, and prodigious translator of verse. The introduction discusses his significant role in the development of Slavic and East European studies in Canada, as founder of the Humanities Research Council of Canada, and as an early promoter of multiculturalism in Canada. In his speech, Kirkconnell discussed his personal encounter with Slavic studies and the early development of the field in Canada, his role in the pre-history of the Canadian Association of Slavists, and the importance he accorded to fostering critical knowledge of the Slavic and East European societies and cultures in Canada. Slavic studies, he argued, were necessary both intellectually and politically: the Slavic and East European literatures constituted “major stones in the arch of modern civilization”; moreover, in the atmosphere of the Cold War, knowledge of the languages and societies of Soviet-dominated Central and Eastern Europe would play a fundamental role in the fight against communism.

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)0.000
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 score0.581
Threshold uncertainty score0.744

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.051
GPT teacher head0.250
Teacher spread0.200 · 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

Citations0
Published2016
Admission routes4
Has abstractyes

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