Identifying and Supporting the Needs of Canadian Armed Forces (CAF) Families in Schools
Bibliographic record
Abstract
In 2017, the Government of Canada released a new defence policy entitled Strong , Secure , Engaged . While Canadian Armed Forces (CAF) personnel are the primary focus of this new defence policy, military families are recognized within this policy as a major source of support and strength for CAF members. Understanding that Canadian military families need access to the support and services they deserve, the development of a Comprehensive Military Family Plan will bring improvements to existing systems of care and services. The purpose of this qualitative study is to explore the types of needs CAF families have within schools while also mapping the landscape of existing supports for CAF families within schools. Using a phenomenological approach, the first phase of the study will explore the types of needs CAF families have within schools. Guided by a multiple embedded case study design, the second phase of the study explore how the needs of CAF families are currently being supported. Multiple forms of data will be collected. This research has the potential to make a national contribution as the findings could be used to help inform the development of policy and programming that is reflective of the actual needs of CAF families.
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.035 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".