Bibliographic record
Abstract
International migration flows and patterns shaped by the determinants, processes and outcomes of social, political, and economic conditions have led to important transformation of society and human geographies. As Canada continues to effectively manage its immigration system and uphold its commitment to international refugee protection and resettlement, it is critical for Canada to do so with an understanding of the changing context of immigration, which are reinforced by shifting policies and their impact, in our contemporary society. In this thesis, the migration trajectory of three groups of newcomers to Canada; international students, Syrian refugees, and refugee youth, are explored by examining policies and conditions that can create group risks and vulnerabilities in immigration, settlement, and integration as groups transition to life in Canada after arrival. As suggested by Castle (2010) migration researchers can advance the field by embedding their work in broader theories of social change to facilitate understanding of the complexity, interconnectedness, variability, contextuality, and multi-mediation of migratory process in the context of rapid change. This thesis employs a geographical lens of place to deepen understanding of processes and outcomes in our contemporary society, while responding to these evolving contexts in one mid-size, post-industrial Canadian city. In three separate research, this thesis examines: 1) economic immigration flow under Express Entry in 2015 and 2016; 2) the role of the voluntary sector during the Syrian Refugee Resettlement Initiative in Hamilton, Ontario in 2016; and 3) the place of school-based settlement in bridging and brokering school-based mental health for newcomer youth.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.009 |
| Science and technology studies | 0.046 | 0.012 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".