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Canadian Studies in the Czech Republic and Central Europe

2020· article· en· W3092430929 on OpenAlexaboutno aff
Don Sparling

Bibliographic record

VenueAd Americam · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsCzechContext (archaeology)RetrenchmentPolitical scienceOutreachGovernment (linguistics)Economic growthEconomic historyGeographyPublic administrationHistoryLaw

Abstract

fetched live from OpenAlex

This article surveys the development of Canadian Studies in Czechoslovakia/the Czech Republic from 1985 (the year the first such course was offered at a Czech university) down to the present. It also deals with the wider context of the development of Canadian Studies in Central Europe under the aegis of the Central European Association for Canadian Studies, established in 2003 with its Secretariat located at Masaryk University, Brno. In both the Czech Republic and the wider region, the late 1990s saw a steady growth in Canadian Studies, fostered by financial support from the Canadian government and outreach activities by Western European Canadian Studies associations. The first decade of the twenty-first century saw an explosion of activities - many new courses and degree programmes, conferences and specialized seminars, international projects, publications, the launching of the Central European Journal for Canadian Studies. The century’s second decade, however, has witnessed retrenchment, the result of systemic changes in higher education systems and the Canadian government’s cancellation of all support for Canadian Studies activities in 2012. Nevertheless, in both the Czech Republic and Central Europe, Canadian Studies continues to enjoy a significant and respected presence in the higher education sphere.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.094
Threshold uncertainty score0.680

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.018
Science and technology studies0.0160.006
Scholarly communication0.0110.002
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.045
GPT teacher head0.279
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), 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
Published2020
Admission routes1
Has abstractyes

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