Temporary Families? the Parent and Grandparent Sponsorship Program and the Neoliberal Regime of Immigration Governance in Canada
Bibliographic record
Abstract
The Canadian government has introduced a series of policy changes to various immigration programs since 2008. This paper focuses on the revamping of the parent and grandparent (PGP) sponsorship program and the introduction of new measures such as the Super Visa. Using Foucauldian analytical tools and drawing on Bacchi’s (2009, 2012) method of studying policy as problematizations, we first historicize the problematization of the family in immigration policy. Second, we refute the government’s representation of immigration under the PGP program problems as essentially a transparent “problem of math,” that of too many applicants overwhelming the system. Finally, we analyze neoliberal technologies of immigration governance and their impact on citizenship formation and struggles. Who counts as family, we argue, has been biopolitically determined in Canadian immigration policy. Family members are recognized as such when it suits the needs of the state. The latest changes in family sponsorship policies objectify potential parents and grandparents reunification applicants, seeing them as human liabilities that pose risks to the Canadian population because of their advanced age. The new measures deploy a neoliberal regime of governance that discriminatorily responsibilizes the family, marketizes regulation, and maximizes the state’s control of the border and of the population.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.012 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".