Putin’s War: Supporting International Students During Global Crises
Bibliographic record
Abstract
At a moment when the members of education communities around the world are working to find a way to live with COVID-19, internationalization of higher education (IHE) communities have also been challenged by Russian President Vladimir Putin’s decision to wage a war against Ukraine. When it is expected from international educators to reimagine international education in a way that is equitable and inclusive (de Wit & Jones, 2018), anti-racist (Buckner et al. 2021), anti-colonial (Beck & Pidgeon, 2020), and sustainable (Shields, 2019), Mr. Putin’s war is unnecessarily taking IHE communities away from these critical conversations. This situation forces international educators to think about a) what will be the world order due to this invasion, and b) how IHE communities will adjust to the new global political realities? In Canada, we are also thinking about how we best show up for international students from Ukraine and Russia, and what are the ways we can support refugees who are being deprived of a post-secondary education due to Putin’s invasion.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".