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Record W2788688437

Female Brazillian students' experiences at Canadian post-secondary institutions

2017· dissertation· en· W2788688437 on OpenAlexfundaboutno aff
Jonathan Burnham

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
FundersLakehead University
KeywordsMathematics educationPolitical scienceMedical educationGender studiesPedagogyPsychologySociologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

This qualitative study investigated the experiences of Female Brazilian international
\nstudents studying in Canadian post-secondary institutions. While funds and research have been
\ninvested in the promotion and marketing of post-secondary institutions to Brazilian international
\nstudents, little or no research has been conducted regarding the cultural accommodations and
\nneeds once they attend these institutions. This phenomenological study examines the experiences
\nof eleven female Brazilian international students between the ages of 26 and 43 who had
\npreviously completed post-secondary education in their own country. Eleven unstructured
\ninterviews, yielded six themes from a grounded theory analysis process: (a) the Competitiveness
\nof the Immigration Process; (b) the Adjustment to Living in Canada; (c) the Challenges of
\nStudying in Canada; (d) Financial Issues; (e) Employment in Canada; and (f) Personal
\nWellbeing. The overall benefits and challenges of studying in Canadian post-secondary
\ninstitutions are presented and recommendations are made describing specific ways in which
\ninstitutions can adapt policies and programs in order to enhance international students? transition
\nto Canada.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.072
GPT teacher head0.414
Teacher spread0.342 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes2
Has abstractyes

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