MétaCan
Menu
Back to cohort
Record W2071202540 · doi:10.3167/foc.2007.490106

Speaking of citizenship

2007· article· en· W2071202540 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFocaal · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIdeologyCitizenshipRestructuringPoliticsWelfare stateLanguage policyPolitical economySociologyContext (archaeology)Political scienceCommodityState (computer science)Public administrationEconomic systemEconomicsMarket economyLaw

Abstract

fetched live from OpenAlex

The Dutch language has become the key technology of the Netherlands' new integration and immigration policy regime. Given the impassioned debates that accompanied language-planning policies in the 1980s, what is most remarkable about the stringent new language policy initiatives is the consensus regarding their necessity. This article analyzes the most ambitious program of the integration regime, inburgering, in the context of the transition to a post-industrial economy and the concomitant restructuring of the labor market. Introduced under the Third Way social democrats in the mid-1990s, the inburgering program was designed to produce the literate laborer of late modernity. This article traces the shift from the 'one nation, one language' ideology associated with welfare state forms of governance to the 'language as commodity' ideology promoted by the Third Way regime. I argue that the inburgering program acted as the Trojan horse of integration politics, introducing the necessity for Dutch language skills into an integration regime that has become the basis for a new politics of exclusion under the current neo-conservative administration.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.842
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.115
GPT teacher head0.496
Teacher spread0.381 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it