Shifting the Resilience Narrative: A Qualitative Study of Resilience in the Canadian Post-secondary Context
Bibliographic record
Abstract
Resilience has been championed as important for mitigating stressors and challenges experienced by students during post-secondary education, as evidenced by the abundance of programs aimed at enhancing student resilience. Despite growing attention to resilience, there continues to be a lack of consensus about the definition or operationalization of the concept. Even less is known about how to foster resilience in the post-secondary context, especially for marginalized or underrepresented students, who are recognized to be at increased risk for negative mental health outcomes during their post-secondary education. To address these gaps, we employed qualitative methodology to explore marginalized or underrepresented students’ perceptions of resilience. Findings demonstrated that resilience arises from a complex and dynamic interplay between personal skills and attitudes and resources available within students’ communities. Post-secondary institutions are called to shift from individual student responsibility to a collective and shared responsibility for students’ wellbeing in the face of adversity.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.040 | 0.023 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".