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Record W2575536623 · doi:10.4000/brussels.1323

Access to the educational institutions of communities whose language is fragile: a Canadian perspective

2016· article· en· W2575536623 on OpenAlexaffabout
Marie Mc Andrew

Bibliographic record

VenueBrussels Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité de Montréal
FundersInnoviris
KeywordsLimitingRelevance (law)Perspective (graphical)Vulnerability (computing)SociologyControl (management)Public relationsPolitical scienceLawEconomicsComputer security

Abstract

fetched live from OpenAlex

After examining certain elements in the debate regarding the control of access to the educational institutions of communities whose language is in a fragile situation, the author presents the contrasting choices made in this respect over the past forty years by the French-speaking minority in Canada depending on whether or not it has the status of regional majority, as well as some of the consequences. The Canadian experience illustrates two approaches, namely that of the protection of a fragile minority by limiting access to the educational institutions it controls to people who have a historical or special connection to the language which defines it, or the dynamic use of schooling in an objective to transform ethnolinguistic relationships. Both approaches have some relevance. However, the first is clearly defensive and should be limited to groups whose vulnerability – which is not historical yet nevertheless present – is still recognised. The second has many more advantages and testifies to a dynamic definition of belonging and culture, which guarantees significant future development.

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)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.777
Threshold uncertainty score0.901

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0540.033
Scholarly communication0.0130.004
Open science0.0020.006
Research integrity0.0040.005
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 head0.086
GPT teacher head0.387
Teacher spread0.301 · 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

Citations0
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueBrussels StudiesSame topicCanadian Identity and HistoryFrench-language works237,207