Inner Border Making in Canada: Tracing gendered and raced processes of immigration policy changes between 2006 and 2015
Bibliographic record
Abstract
The Canadian immigration system went through significant changes under the previous Conservative government (2006–2015). This paper examines official narratives in the Citizenship and Immigration Canada (CIC) documents related to two policy changes: 1) Conditional permanent residency for the spousal sponsorship program, and 2) Bill C-43: Faster Removal of Foreign Criminals Act. Drawing on critical race readings of Canadian nation building and critical border literature that re-conceptualizes borders as processes and multidimensional, this paper examines the discursive narratives that enabled bordering practices to shift inward during the previous Conservative government era. My focus on the discursive processes sheds light on linkages between bordering practices and the historical construction of Canada as a white settler nation. I demonstrate the ways in which exclusionary policy developments constructed ‘inner borders’. I argue that the bordering practice at play in these policy changes were only possible through two discursive conditions and functions: 1) the naturalization of the gendered and racialized exclusions built into Canadian national membership, and 2) the erasure of historical and systemic injustice embedded in the Canadian immigration system and Canadian nation-building project as a whole. Through the naturalization and erasure of historical and systemic injustice, “inner borders” became “invisible borders, situated everywhere and nowhere” (Balibar, 2002, p. 78), pushing immigrant women and the racialized community into further precariousness.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.031 | 0.014 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".