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Record W1874093110 · doi:10.47678/cjhe.v43i1.2219

L’expérience sociale des institutions scolaires : construire son identité linguistique au fil de la transition à l’enseignement supérieur

2013· article· en· W1874093110 on OpenAlexaffvenueabout
Marie‐Odile Magnan

Bibliographic record

VenueCanadian Journal of Higher Education · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsSociologyIdentity (music)Gender studiesInstitutionTransition (genetics)Social mobilityField (mathematics)Sociological researchSocial identity theoryHumanitiesPedagogySocial scienceSocial group

Abstract

fetched live from OpenAlex

Rather than using the classical view generally embraced by the field of sociology of education – that is equity in educational chances and mechanisms of social reproduction, this article analyses the construction of linguistic identity among young adults during their school and mobility pathways. The results obtained from this qualitative research (N=33) demonstrate that the transition to higher education influences the construction of linguistic identity of young adults who previously attended a minority linguistic school in Canada – and this is mainly due to the new relationships to otherness that the transition to higher education involves. Using a micro sociological and constructivist approach, the article draws a parallel between the objective pathways (school and mobility transitions) and the subjective pathways (construction of linguistic identity) of young adults by analysing their life story with a diachronic approach. Although some researchers have evoked the decline of the school institution (Dubet, 2002), this article reveals that the social experience of school leaves a mark on life pathways.

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)0.004
metaresearch head score (Gemma)0.004
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 score0.464
Threshold uncertainty score0.934

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0170.031
Scholarly communication0.0110.006
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.289
Teacher spread0.276 · 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
Published2013
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Higher EducationSame topicCanadian Identity and HistoryFrench-language works237,207