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Record W7114780180 · doi:10.7202/1121531ar

Impact de la crise de la COVID-19 sur les familles francophones dans les Prairies canadiennes

2025· article· fr· W7114780180 on OpenAlexaffvenueabout

Bibliographic record

VenueMinorités linguistiques et société · 2025
Typearticle
Languagefr
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of CalgaryUniversity of AlbertaUniversité de Saint-BonifaceUniversity of Saskatchewan
Fundersnot available
KeywordsFrenchContext (archaeology)Vulnerability (computing)Politics

Abstract

fetched live from OpenAlex

Contexte et but. Dans le contexte linguistique minoritaire où l’accès à des services en français est un défi, l’étude voulait documenter dans quelle mesure la crise de la pandémie avait eu un impact sur les familles francophones au Manitoba, Saskatchewan et Alberta. Méthodes. À partir des informations recueillies lors de 6 World Café du Monde, un sondage a été créé et distribué en ligne aux membres d’organismes francophones dans ces provinces. Des analyses descriptives et de régression ont été menées. Résultats. Des 319 familles, la grande majorité a reconnu l’impact négatif et anxiogène de la pandémie. Plusieurs facteurs de risque ont été identifiés : une compréhension moyenne ou faible de l’anglais, la déconnexion avec la communauté francophone locale, la difficulté de vivre en français en famille et de suivre la scolarité de ses enfants à la maison. Conclusion. La pandémie a été un défi pour les familles francophones des Prairies. Des ressources accrues en français et des politiques de soutien sont recommandées.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.052
GPT teacher head0.483
Teacher spread0.431 · 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 designObservational
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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