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Record W1974544076 · doi:10.1353/dsp.0.0011

Immigration, Integration, and Anxiety in Germany

2005· article· en· W1974544076 on OpenAlexaff
Robin Ostow

Bibliographic record

VenueDiaspora A Journal of Transnational Studies · 2005
Typearticle
Languageen
FieldArts and Humanities
TopicGerman Colonialism and Identity Studies
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsTurkishGermanCitizenshipImmigrationContext (archaeology)PoliticsSituatedSettlement (finance)SociologyPolitical scienceGender studiesPolitical economyHistoryLaw

Abstract

fetched live from OpenAlex

Ostow ’s review essay addresses two recent books by the scholars Ruth Mandel and Joyce Marie Mushaben that deal with Turkish migration and partial integration in Germany. She outlines how the lenses of these authors’ respective disciplines—political science and cultural anthropology—shape their different but potentially complementary understanding of Turkish guest-workers and their families and descendants, and how the analysis of the politics and culture surrounding their arrival and eventual settlement in Germany must be situated in the context of the larger waves of flight, resettlement, and labor recruitment that have brought 20 million newcomers who have stayed on in Germany since the end of World War II. She argues that Germany became a country housing diasporas while lacking a properly nuanced set of admission, citizenship, and cultural absorption policies. She praises and details the advantages both of Mushaben’s approach, which compares the experience of quite diverse immigrants (Italian, Polish, and German in addition to Turkish), and Mandel’s, which deals with smaller histories and interfaces—“spaces of interaction”—where German and Turkish and sometimes other cultures meet.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.034

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 studies0.0020.004
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
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 head0.026
GPT teacher head0.264
Teacher spread0.238 · 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 designQualitative
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

Citations0
Published2005
Admission routes1
Has abstractyes

Explore more

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