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Record W2274274538 · doi:10.1080/13876988.2015.1095429

“The Good, the Bad and the Ugly” Reconsidered: A Comparison of German, Canadian and Spanish Labour Migration Policies

2015· article· en· W2274274538 on OpenAlexaboutno aff
Claudia Finotelli, Holger Kolb

Bibliographic record

VenueJournal of Comparative Policy Analysis Research and Practice · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationGermanSkepticismPoliticsImmigration policyEconomicsMigrant workersPolitical sciencePolitical economyLabour economicsEconomic growthLawGeography

Abstract

fetched live from OpenAlex

This article compares three immigration countries that are perceived, both publicly and politically, as being fundamentally different: Canada, which is allegedly one of the most attractive destination countries for labour migrants worldwide; Germany, which is still thought to be sceptical towards immigration; and finally Spain, which is considered institutionally incapable of implementing efficient labour migration policies. Against the backdrop of various political reforms that have been adopted in these countries, however, the article argues that such a distinction is becoming increasingly inaccurate. This observation is backed empirically by analysing the technique of screening labour migrants and the temporal design of labour migration policy.

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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.326

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0060.007
Scholarly communication0.0080.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.197
GPT teacher head0.530
Teacher spread0.334 · 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 designObservational
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

Citations20
Published2015
Admission routes1
Has abstractyes

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