No Return Ticket: CBSA Deportation in Canada
Bibliographic record
Abstract
Viewed through the theoretical lens of securitization theory & moral regulation, this thesis examines deportation and detainment in Canada across CBSA jurisdictional regions. Furthermore, this thesis attempted to explain how deportation and detainment trends changed since 2005, and what may be possible causes. Being a descriptive analysis study, this thesis utilizes a documentary research methodology to gather data, while using current literature to explain border security and deportation in Canada—bolstering results from the analysis on deportation and detainment statistics. The findings from the results ultimately provide new insight for CBSA, as well as for future research into the efficacy of operations of CBSA and the status quo on border security. \n \nFindings from this thesis show deportation rates, across the majority of CBSA jurisdictional regions, have been steadily declining since 2005. Furthermore, it was found as deportation rates decline, average days detained and detention rates have increased nationally since 2005. Although this thesis was able to answer its research question in part, it was not able to answer any causes of change because of a lack of literature on the topic—which is a gap of knowledge future researchers can address.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".