The Revaluation of the National Language in a Post-National Era: Language Policy and the Governance of Migration and Citizenship
Bibliographic record
Abstract
This dissertation examines the influence of neo-liberal discourses and strategies of governance on a revaluation of the national language, in the form of formalized requirements and testing of language proficiency, within immigration, integration, naturalization, and citizenship policy in Canada and the United Kingdom. Employing an interdiscursive language policy analysis (da Silva & Heller, 2009), the dissertation combines textual analysis of policy documents, informed by the principles of Critical Discourse Analysis (CDA), with an ethnographic understanding of the policy process gathered through interviews with policy actors. It applies the key CDA analytical categories of emergence, selection, operationalization, and materialization of discourses within domains of social action, and recontextualization of discourses across domains (Fairclough, 2009; Wodak & Fairclough, 2010) to a comparative case study of the policy processes surrounding language, immigration, and citizenship in Canada and the UK. \nThe analysis of the cases reveals how neo-liberal discourses of the knowledge-based economy and communitarian discourses of cohesion and active citizenship have been recontextualized within the domains of immigration and citizenship policy, ultimately constituting a similar hegemonic discourse on the importance of language skills in a common, national language for immigrant integration. Further, the operationalization and materialization of this discourse is interpreted, drawing on the field of governmentality studies, as instantiating an advanced liberal political rationality (Rose, 1996, 1999), with formal language requirements and tests serving as political technologies for the subjectivation of prospective citizens. It is also revealed, however, that contestation over, and contradictions within this neo-liberal strategy of governance have shaped the particular policies regarding language, immigration, and citizenship in each case. \nThe dissertation contributes to the literature on language testing practices for immigration and citizenship by identifying the motivation for such practices in the political economy of contemporary globalization and neo-liberal state strategies for the governance of immigration, integration, and citizenship. It also contributes to the field of Language Policy and Planning (LPP) by suggesting a theoretical and methodological framework for the study of state language policies in a neo-liberal, post-national era.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".