The Rights and Realities of War-affected Refugee Children and Youth in Quebec: Making Children's Rights Meaningful
Bibliographic record
Abstract
Each year, thousands of children enter Canada, fleeing from countries where there has been armed conflict. In Quebec alone, between 1998 and 2007, 8 of the top 10 source countries for accepted refugees were war-affected nations, representing 34,838 people, including children. Yet, this group has been largely overlooked in Canadian research, policy and service provision. This paper traces the lived realities and resettlement experiences of a sample of war-affected children and youth living in Quebec who arrived accompanied by a parent or caregiver, alone as refugees, or without documented legal status, seeking asylum. Drawing upon in-depth interviews with 22 war-affected youth, the paper considers youth's perspectives on the lasting war-related distress experienced in Canada. The paper critically identifies the impact of the UNCRC on their lives in their countries of origin, in their resettlement to Canada, as well as Canada's role and obligations in meeting the needs and rights of this unique population. The paper concludes with a discussion of the implications for policy and practice, particularly with regard to envisioning ways of better meeting the rights of war-affected children.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".