Examining the Academic Experiences of Korean Immigrant Students at Universities in Toronto
Bibliographic record
Abstract
The Korean population is consistently growing in Canada. My master’s thesis is motivated by the lack of academic literature on the experiences of Korean immigrant students in Canadian postsecondary institutions. This research examines their experiences, including the challenges and strategies they develop. Immigrant students have been known to struggle with language and cultural differences, yet, institutions are still lacking support system to accommodate immigrant students. The concept of intellectual development and self-authorship are applied to analyze the challenges of students and their growth from developing strategies in overcoming their challenges. This research is approached as multiple case studies, examining Korean immigrant undergraduate students, who have moved to Canada during high school. Two cases are examined to compare the academic experiences of students studying the sciences and humanities disciplines. Data are being collected by conducting three semi-structured interviews with participants, including individual and focus group interviews, and participant journals for their ongoing reflection. This research is expected to be completed by January 2019, and it aims to contribute in finding better means to provide equitable opportunities for all students with diverse needs.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".