Introduction: migrant mothers challenging racialized citizenship
Bibliographic record
Abstract
This article introduces the Special Issue on Migrant Mothers’ Creative Interventions into Racialized Citizenship. It reflects on the theoretical and policy areas to which research on migrant mothers’ citizenship can contribute. The introduction argues that studies on citizenship, racialization, migration are important to theoretical as well as policy debates on contemporary nationhood, multiculturalism, generational and social cohesion as well as austerity and racism and migration. Drawing on our own work, as well as contributions to the Special Issue, the introduction illuminates this with respect to examples from the US, Canada, Portugal and the UK. These issues are relevant to migrants of different statuses including skilled migrants, family migrants, undocumented migrants and asylum seekers. The migrant mothers’ care and cultural work in bringing up their children can be theorized as a creative intervention challenging racialized citizenship.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.021 | 0.004 |
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".