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Record W4241882830 · doi:10.22215/etd/2019-13766

Hidden Voices in Transnationalism: International Post-Secondary Student Experiences of Precariousness and Belonging in Ottawa

2019· dissertation· en· W4241882830 on OpenAlexaffabout
Dzifa Binka

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsTransnationalismCitizenshipImmigrationPolitical scienceGender studiesAffect (linguistics)FeminismSociologyPedagogy

Abstract

fetched live from OpenAlex

International post-secondary students have been highlighted as potential solutions to the skill and talent gaps in the Canadian economy by federal and provincial governments.Despite this, there are gaps in the literature surrounding these students in relation to their lived experiences during their stay.By applying a theoretical framework composed of transnational feminism, precarious immigration and belonging and citizenship literature, this study contributes to the current research by exploring the factors that affect the experiences of international students.Additionally, through semi-structured interviews with international students and associated staff at Carleton University and policy analysis, this study investigates whether federal, provincial and post-secondary institutions are instrumental in producing a sense of belonging or precariousness for these students.The findings indicate that though there are many resources available to foster a sense of belonging and safety, the lack of integration and knowledge across institutional scales produces precarious environments for international students.Key words: international post-secondary students, belonging and citizenship, security and wellbeing, racialization, transnational migration Students' Association for being such willing participants and helpers in this project.Without all of you, this study could not have happened, and I am truly grateful.Thank you to my supervisor, Dr. Jennifer Ridgley, for your guidance throughout this process.Without you, I would not have been able to accomplish this feat or even begin this program.Your support and generosity were the reasons I was able to come to Canada and start this process, and you have been an amazing encouragement throughout these last two years.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.341
Threshold uncertainty score0.685

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0250.014
Scholarly communication0.0090.002
Open science0.0020.010
Research integrity0.0010.005
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 head0.007
GPT teacher head0.311
Teacher spread0.304 · 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
Published2019
Admission routes2
Has abstractyes

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