Considerations for supporting Canadian military-connected students in K-12 and higher education
Bibliographic record
Abstract
LAY SUMMARY Within Canada, little is known about the educational experiences of military-connected students in the K-12 and higher education systems. American research has been published and provides insight into the unique challenges that military-connected students can experience in such contexts. Because of the lack of research conducted in Canada to date, it is unclear if American research findings represent the educational experiences of Canadian military-connected students in K-12 and higher education. This article discusses how identification of military-connected students, as well as educator awareness, or lack thereof, are creating organizational challenges in the Canadian context for supporting military-connected students in K-12 and higher education.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.035 | 0.006 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.022 | 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".