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Record W6980831464

Cultural Capital during Migration—A Multi-level Approach for the Empirical Analysis of the Labor Market Integration of Highly Skilled Migrants

2006· article· en· W6980831464 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2006
Typearticle
Languageen
FieldEngineering
TopicMining Techniques and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsProsperityImmigrationResidenceContext (archaeology)Order (exchange)Market integrationEmpirical researchHuman capital
DOInot available

Abstract

fetched live from OpenAlex

The integration of highly qualified migrants into the labor market can be an opportunity for knowledge societies because their prosperity depends on the incorporation and improvement of cultural capital. In this paper we present a qualitative research approach with which we analyze on several levels how migrants make use of their cultural capital during their entry into the labor market: in addition to the biographical experience of migrants we analyze how this experience is embedded in milieus, social networks and self-organizations (meso-level) and structured by the macro-level of judicial regulations of immigration and labor market policies. Our empirical analysis is focused by the assumed importance of educational qualification and residence status during entry into the labor market. Four different groups of empirical cases, which differ with respect to the level of education, the place of its acquisition (at home or abroad) as well as to their residence status, are compared to each other. In order to study the contingencies of meso and macro-social contexts, labor-market integration will be examined in the context of Germany as well as in Canada, Great Britain and Turkey. URN: urn:nbn:de:0114-fqs0603143

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.270
GPT teacher head0.481
Teacher spread0.211 · 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 teacher head, 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

Citations0
Published2006
Admission routes1
Has abstractyes

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