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Record W2565571456 · doi:10.7202/1036422ar

Being a Francophone Parent with Children in Dutch-medium Education in Brussels

2016· article· en· W2565571456 on OpenAlexvenueno aff
Luk Van Mensel

Bibliographic record

VenueMinorités linguistiques et société · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsFrenchIdentity (music)AppealMedium of instructionSociologyNationalismPolitical sciencePedagogyLinguisticsLaw

Abstract

fetched live from OpenAlex

In the officially bilingual (French–Dutch) Brussels Capital Region (Belgium), education is largely organized in two parallel but separate systems: French-medium education and Dutch-medium education. Parents must choose to send their children to either a Dutch- or a French-medium school. The choice of one education system over another may generate identity-related issues, such as the idea—rooted in nationalism—that “being a French speaker” and “sending your children to Dutch-medium education” are identity options that are by definition conflicting. In this article, I present a case study of a Francophone couple who decided to enroll their children in a Dutch-medium school in Brussels. Even if this decision brought the parents closer to Dutch-speaking social networks, it also highlighted the tensions and contradictions between the various identity options available. The study shows how these parents, in trying to deal with these tensions, appeal to quite different and sometimes contradictory discourse on language and belonging.

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)0.002
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 score0.368
Threshold uncertainty score0.732

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0150.004
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.002
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 head0.031
GPT teacher head0.445
Teacher spread0.414 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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