School Absenteeism Among Immigrant and Refugee K-12 Students in Canada: A Scoping Review
Bibliographic record
Abstract
School attendance problems (SAPs) are a growing concern among K-12 students in Canada and have serious long-term consequences. Immigrant and refugee students face additional challenges that may increase their risk of absenteeism. However, research on this topic remains limited. This scoping review aimed to map and synthesize the existing research in Canadian literature among immigrant and refugee K-12 students in Canada, with objectives to explore the nature and quantity of the studies, examine how SAPs have been conceptualized and measured, and finally, identify knowledge and research gaps. Following the PRISMA-ScR guidelines, a comprehensive search was conducted across major databases and using snowballing techniques. Thirty-two studies published between 2003 and 2024 met the inclusion criteria. Findings revealed that school dropout and exclusion were the most frequent and explicit SAP-related themes, while other SAP types (school refusal, school withdrawal and truancy) were rarely addressed explicitly. SAPs were secondary findings in the majority of the studies and were often not conceptualized or labeled; instead, descriptions of the students’ SAP experiences were presented in study findings. Although beyond the parameters of this review, findings also signal that exclusionary practices may be a primary and pervasive experience for many immigrant and refugee students. The findings highlight the need for more research that explicitly examines different SAP types within this population to understand both their prevalence and the lived experiences associated with them, including differences across generational immigration status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".