Unaccompanied/Separated Minors and Refugee Protection in Canada: Filling Information Gaps
Bibliographic record
Abstract
This paper fills information gaps with regard to unaccompanied/ separated minors in Canada. By the means of reviewing Citizenship and Immigration Canada administrative databases, it investigates how many unaccompanied/separated refugee minors exist, who they are, and how they are received in Canada.We found that there were fewer truly unaccompanied minors than previously reported. In the asylum stream, only 0.63 per cent (or 1,087) of the total claimant population were found to be unaccompanied by adults in the past five years. In the resettlement stream only two truly unaccompanied minors were resettled during 2003 and 2004. Regarding their socio-demographic characteristics, we found that unaccompanied minors compose a highly heterogeneous group from many different countries. Regarding how they were received in Canada, very little evidence existed. Our study found that unaccompanied and separated asylum-seeking minors showed a higher acceptance rate and quicker processing times than the adult population, but details about the minors’ actual reception into Canada remains to be further explored. This study recommends that Citizenship and Immigration Canada review its administrative databases with a view toward improving the data about separated/unaccompanied children. Consistent and detailed definitions are required to develop a comprehensive policy framework for unaccompanied/ separated minor refugees in Canada.
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 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 | 0.012 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.025 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 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".