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Record W2486629339 · doi:10.1017/cbo9780511626494.001

Introduction: Deportation and the State

2009· book-chapter· en· W2486629339 on OpenAlexaff
Antje Ellermann

Bibliographic record

VenueCambridge University Press eBooks · 2009
Typebook-chapter
Languageen
FieldArts and Humanities
TopicHistorical and Contemporary Political Dynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCoercion (linguistics)BureaucracyState (computer science)EnforcementDeportationPolitical sciencePopulationMeaning (existential)Law and economicsCompliance (psychology)LawSociologyComputer scienceEpistemologySocial psychologyPsychologyPoliticsPhilosophy

Abstract

fetched live from OpenAlex

The connection between the state and its population has been particularly complex, if for no other reason … than the modern state in its rules and laws has demanded so much from people. … Of course, coercion and the threat of coercion, by most definitions, lie at the center of the meaning of the state and its demands for compliance by its population. … But it is simply impossible for a state to achieve tractability by relying exclusively on its judges and jailers. No matter how vaunted the bureaucracy … state leaders could easily find their institutions quickly overwhelmed by the enormity of the task of enforcement, even with vast bureaucracies. (Migdal, 2001, p. 251) The final decades of the twentieth century have been marked by the progressive expansion of the socially coercive state in the advanced industrialized world. Beginning in the 1980s and extending into the new millennium, liberal democracies faced public demands for hard-edged social regulation in areas such as migration control, criminal justice, and homeland security. In response, elected legislatures enacted far-reaching measures of social control across a range of policy fields and funded the rapid growth of coercive bureaucracies. To illustrate this point, from 1991 to 2001 the budgets of both the German Federal Border Police and the Canadian immigration service more than doubled, whereas the U.S. Immigration and Naturalization Service's budget nearly quadrupled. Even more dramatically, immigration spending in Britain in the same period underwent a more than sixfold increase. Significantly, these law enforcement initiatives have not been limited to the regulation of migration. In the area of drug control, the budget of the U.S. Drug Enforcement Administration more than tripled between 1985 and 2002. In the field of criminal justice more generally, U.S. government spending on the federal prison system more than quadrupled between 1985 and 2002. Similarly, in Canada, the corrections and rehabilitation services budget doubled from 1989 to 2002. In North America, governments simultaneously enacted sweeping administrative reforms.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.017
Threshold uncertainty score0.055

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 studies0.0030.008
Scholarly communication0.0040.003
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.017
GPT teacher head0.163
Teacher spread0.146 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2009
Admission routes1
Has abstractyes

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