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Record W4319040150 · doi:10.47678/cjhe.vi0.189469

“I didn’t know what to do, where to go”: The voices of students whose parents were born in Latin America on the need for care in Quebec universities

2022· article· en· W4319040150 on OpenAlexaffvenueabout
Roberta Soares, Marie‐Odile Magnan

Bibliographic record

VenueCanadian Journal of Higher Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Practises and Engagement
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsBlameLatin AmericansInstitutionCraftInterpretation (philosophy)Social capitalPedagogySociologyQualitative researchMedical educationPsychologyCultural capitalHigher educationGender studiesPolitical scienceSocial scienceSocial psychologyMedicineLawHistory

Abstract

fetched live from OpenAlex

This qualitative study reports the university experiences of Quebec students whose parents were born in Latin America. The analysis, which looks at students who have either persisted in school or discontinued their studies, underscores the importance of cultural capital and, especially, an understanding of the student craft for school retention. The students report a low sense of affiliation with the university, and a perceived lack of support and care from the university and its social actors. Our interpretation of the data highlights self-blame for the challenges faced in university concurrently with the implementation of strategies to meet the challenges of the institution. We conclude by emphasizing how important it is for universities to support students better, adequately inform them about their options and the institution’s inner workings, and form a community with students in a spirit of care.

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)0.006
metaresearch head score (Gemma)0.009
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 score0.972
Threshold uncertainty score0.544

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0220.011
Scholarly communication0.0060.003
Open science0.0030.004
Research integrity0.0030.005
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 head0.021
GPT teacher head0.335
Teacher spread0.314 · 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
Published2022
Admission routes3
Has abstractyes

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