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Record W2788815043

Ethno-linguistic peculiarities of French Canadian and English Canadian linguistic world-images in comparative aspect

2017· article· en· W2788815043 on OpenAlexaboutno aff
Albina Rishatovna Mordvinova

Bibliographic record

VenueJournal of Fundamental and Applied Sciences · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicLexicography and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPhraseologyLinguisticsHomelandFrenchWorld EnglishesHistorySociologyPoliticsPolitical scienceLawPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

In this article, the ethno-linguistic features of French Canadian and English Canadian linguistic world-images are subjected to comparative analysis. As the result of the mentioned linguistic world-images comparison according to a number of criteria, the author comes to conclusion that there is a significant number of differences between them. First of all, these differences come from the peculiarities of English and French Canadians’ historical paths: for a long time English Canadians and English have dominated in all spheres of public life, whereas francophone minority has been oppressed (which is reflected in idioms), and the use of French was confined to a family circle. The differences in morphological and grammatical features of languages determine the differences in mentality: though the system of tenses (respectively, the mental division of the time space by the nations) is quite similar, a greater analyticity of the English language and a greater linguistic flexibility of French is observed. When English Canadian and French Canadian phraseology is compared, the greater role of religion in the French Canadian community is evident, rather than in English Canadian; the influence of the Canadian variant of the English language on the Canadian variant of French is clearly expressed. With all the differences, both LWI share a number of common (common Canadian) concepts (northness, homeland, etc.) and values (tolerance, peacefulness, discretion, etc.). Key words : linguistic world image, concept, value, phraseology, ethno-linguistic specific feature.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.411

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0090.006
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.048
GPT teacher head0.280
Teacher spread0.232 · 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 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
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Fundamental and Applied SciencesSame topicLexicography and Language StudiesFrench-language works237,207