Bibliographic record
Abstract
Internationalization is an important goal, yet challenging for post-secondary institutions and it calls for an extensive research and planning. However, understanding international students’ lives is not an easy task and needs a meticulous examination of these students’ experiences and relations at the host country. More to the point, making sense of minority students such as Middle Eastern female students is a more challenging and complex venture due to its political sensitivity. My goal as a researcher then, is to provide a clear picture of female students from Middle East in Canada, hoping to help policy makers and educators on their way of making universities a better place for minority international students. An interpretive qualitative case study under a constructivism paradigm will help me to reach my goal with the help of pre-interview activities along with in-depth interviews. Moreover, this study as a hermeneutic study, using reflexive interpretation, being informed by postcolonial theory can shed light to the meanings that Middle Eastern female students attribute to the situations they find themselves in, hoping to pave the way for providing a more just and inclusive educational system for all students.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.036 | 0.006 |
| Scholarly communication | 0.008 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".