Connected from Afar: Culturally Grounded Remote Peer Support During the COVID-19 Pandemic
Bibliographic record
Abstract
In this article, two PhD students from separate Canadian universities, both sharing an immigrant background, engage in autobiographical narrative inquiry, highlighting the importance of peer-support experiences during the pandemic. They explore their journeys as immigrants and PhD students, recounting their experiences in a virtual support group. This narrative illustrates the exchange of academic, mental health and personal support rooted in shared culture, language and ethnicity. The study provides insights into the benefits of peer support on virtual platforms and adds immigrant perspectives. It suggests that university administrators can find innovative ways to support marginalized students, fostering mutual support among them, particularly in the remote-learning context of COVID. This article highlights the potential for authentic and effective support systems that address the unique challenges faced by immigrant and marginalized students, enhancing their academic and personal development.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.027 | 0.011 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".