Responding to student mental health challenges during and post-COVID-19
Bibliographic record
Abstract
During the COVID-19 pandemic, educators around the globe seek to understand how to support students whose academic performance is impacted by mental health challenges. This article presents a co-operative inquiry undertaken by colleagues in Canada and Australia, responding to the question; what insights can the existing Carleton University framework of reflective questions offer to educators responding to student mental health challenges in social work education during the COVID-19 pandemic? The risks and complexities of attending to student mental health needs are illustrated by a pandemic-informed case study that extends the framework into this unique context and illustrates the importance of respecting learning requirements, combating discrimination, protecting students’ rights, and honouring the professional and legislative mandates of social work within all responses aimed at supporting student mental health resilience during COVID-19. This article acknowledges the limitations of previous practices guiding work with students with mental health needs during any period of crisis or disaster and demonstrates that the Carleton University framework assists in developing improved processes and policy grounded in social work’s commitment to social justice and critical reflection.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.019 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 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".