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Record W7159899744

バイリンガル国家カナダの行方 : ケベックは留まるのか?

2011· article· ja· W7159899744 on OpenAlexaboutno aff
Nobuaki Suyama

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2011
Typearticle
Languageja
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsFrenchParliamentIndependence (probability theory)Status quoSovereigntyReferendumPower (physics)Position (finance)
DOInot available

Abstract

fetched live from OpenAlex

Canada, an officially bilingual country, contains two linguistically rather incompatible societies: English and French. The use of two languages has always been permitted in national institutions such as Parliament and the Supreme Court. However, it is only in response to the rise of the independence movement in Quebec that Prime Minister Pierre Elliot Trudeau enacted the policy of official bilingualism throughout Canada in 1969. A bilingual Canada made life much easier for francophone Canadians outside Quebec than before. Also, the unilingual turn of Quebec enhanced the social position of francophone Quebecers inside Quebec. In other words, francophone Quebecers have got the best of both worlds. Quebec had two provincial referendums to ask the residents if they support the independence of Quebec from Canada or not. In the first referendum(1980), the Quebec Party's proposal was soundly dashed with no major imminent threat posed to the Canadian federation. In the second referendum held in 1995, the OUI side for independence came as close as to victory. Since this shocking event, in which Canada seemed to be doomed, the mood for sovereignty has subsided a bit, but the Quebec Party continues to gather support and may be strong enough to grab power in this decade. In the author's view, concerning the language situation, francophone Quebecers should be satisfied with the status quo in a bilingual 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 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)0.010
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.281
Threshold uncertainty score0.565

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.013
Science and technology studies0.0050.002
Scholarly communication0.0140.006
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0890.046

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 head0.050
GPT teacher head0.287
Teacher spread0.237 · 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
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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