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Record W1437315174 · doi:10.1017/cbo9780511804830.017

The Free Economy and the Jacobin State, or How Europe Can Cope with the Coming Immigration Wave

2007· book-chapter· en· W1437315174 on OpenAlexaff
Randall Hansen

Bibliographic record

VenueCambridge University Press eBooks · 2007
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsImmigrationImmigration policyPolitical scienceContradictionPolitical economyImmigration lawState (computer science)Development economicsSociologyLawEconomics

Abstract

fetched live from OpenAlex

Americans and Europeans tell themselves different immigration stories. Although it is in fact exceedingly difficult to migrate legally to the United States, and U.S. immigration policy was shot through with racist intent until the 1960s, immigration is a basic part of the country's founding myths. By contrast, with the partial exception of France, European nation-states did not base their identity on immigration. The point here is conceptual: it was always grating to see scholars, often with undisguised glee at their cleverness, point out the supposed contradiction between Germany's official claim that it was “not a country of immigration” and the reality of substantial migration. There was in fact no contradiction: the statement was about whether Germany derived its identity from immigration and whether immigration was wanted. It did not, and it was not. Neither Germany nor the rest of Europe pursued a policy of encouraging immigration; on the contrary, all European countries pursued until recently the chimerical goal of zero immigration. This is now changing. Since the late 1990s, all governing parties in several European countries – the United Kingdom, France, Germany, Italy, and Spain – have changed their rhetoric, attitude, and policy toward immigration. They have good reason to do so. If the demographers are right (and they have been spectacularly wrong about most things over the last century, so the “if” is not rhetorical), Europe will need much more immigration to stave off population decline.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.007
Scholarly communication0.0060.005
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.029
GPT teacher head0.210
Teacher spread0.181 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2007
Admission routes1
Has abstractyes

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