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Record W3001083767 · doi:10.1177/1477971419898491

Beyond literacy and language provision: Socio-political participation of migrants and large language minorities in five countries from PIAAC R1/R2

2020· article· en· W3001083767 on OpenAlexaboutno aff
Anke Grotlüschen, Svetlana Chachashvili‐Bolotin, Lisanne Heilmann, Gregor Dutz

Bibliographic record

VenueJournal of Adult and Continuing Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsPolitical efficacyLiteracyPolitical scienceSociologyGender studiesPedagogyLaw

Abstract

fetched live from OpenAlex

Integration is more than work and school: It consists of socio-political participation as well. Even without citizen’s rights, migrants have an opinion on whether they ‘have a say’ in the host or dominant society. This expression – having a say – is emblematic, because it is a well-known survey question, also used in the Program for the International Assessment of Adult Competencies (PIAAC). For this article, the authors choose Austria, Canada, Germany, Israel and the USA to analyse variables on political efficacy and volunteering as indicators for socio-political participation. Using post-colonial and multiple literacy approaches, the authors examine whether migrants and language minorities feel heard. Findings show that first-generation migrants in four countries feel low political efficacy and are excluded from volunteering. However, when taking literacy proficiency into consideration, many effects for political efficacy disappear. For large language minorities, however, controlling for literacy has no effect on their socio-political exclusion.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.229

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.005
GPT teacher head0.307
Teacher spread0.302 · 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 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

Citations15
Published2020
Admission routes1
Has abstractyes

Explore more

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