'Borders...Are No Longer at the Border': High-skilled Labour Migration, Discourses of Skill and Contemporary Canadian Nationalism
Bibliographic record
Abstract
This dissertation explores the constitutive relationship between immigration and nationalism as manifest in the high skilled labour market of post-liberalization (post 1960s) Canada. I show that as skilled immigration became crucial for Canadian national prosperity, a simultaneous rise in discourses of skill deficit rendered actively recruited immigrants as deficient worker subjects. Unfolding in the decades following liberalization, persistent discourses of deficit - refracted through a systemic privileging of Canadian/Western skills and training (understood as both tangible credentials and intangible soft/cultural skills) - constructed the figure of the immigrant as a prototypically skill-deficient subject struggling to integrate into the Canadian labour market, and by extension, to the larger Canadian society. Scholarship on labour market integration has frequently seen the issue as an example of policy level and administrative disjuncture. In contrast, I argue that skilled immigrants’ marginalization in the labour market of the very nation that recruited them as vital for national prosperity creates a gap between immigrants’ juridical and substantive membership. It is systematic and socio-politically productive. I conduct a critical discourse analysis of post-liberalization skilled immigration policies and related texts (government commissioned reports, press releases, ministerial speeches, and policy backgrounders) and show how the nation state continues to be an exclusive space where immigrants’ welcome is contingent and conditional on their ability to approximate an amorphous and contested Canadianness. I argue that it is through the mobilization of deficit discourses that the post-liberalization state negotiated its increasing reliance on immigrant labour with the historically racially conceptualized criteria for national membership. In the post- liberalization global hierarchy of nation states, the dynamics of welcome (as labour) and expulsion (from membership) allowed Canada to open up the national space to the raceless meritocracy of the best and the brightest, while continuing to re-align it along racial lines. This dissertation makes three key interventions: 1) it repositions the high skilled labour market – typically considered unfettered by practices of racialized nationalism - as a key site for its exercise in post-liberalization era, 2) it argues that training/learning discourses in this context are better seen as nationalist discourses subsumed within the discriminatory notion of Canadian experience, and finally, 3) it proposes a dialogue between scholarships on Canadian nationalism and immigrants’ labour market integration as the conceptual disconnect between these is analytically costly for our understanding of post-liberalization Canadian nationalism.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.042 | 0.039 |
| Scholarly communication | 0.016 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| 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".