MétaCan
Menu
Back to cohort
Record W2788436169 · doi:10.5539/ijel.v8n3p36

Politics of Immigration and Language: The Case of Pakistani Residents in Spain

2018· article· en· W2788436169 on OpenAlexvenueno aff
María Isabel Maldonado García

Bibliographic record

VenueInternational Journal of English Linguistics · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSouth Asian Studies and Conflicts
Canadian institutionsnot available
Fundersnot available
KeywordsNationalityImmigrationGovernment (linguistics)Political sciencePoliticsOfficial languageState (computer science)LawImmigration lawSociologyLinguistics

Abstract

fetched live from OpenAlex

The new Spanish nationality law requires a certain level of Spanish language proficiency for the application of Spanish nationality. The law, which is on the Official State Bulletin (BOE-Boletin Oficial del Estado) N. 167, Section I, Page 58, 149 and which was drafted on the 14th of July, 2015, came in effect on the 15th of October, 2015. The new regulation outlined the new requirements for the immigrants to be able to become Spanish citizens. The law was mainly targeted towards the descendants of those Jewish people who were thrown out of Spain in 1492 in an effort of the Spanish government to normalize relations. Nevertheless, all new applicants are somehow affected by it since a minimum knowledge of Spanish language is required, (level DELE A2 according to the Common European Framework of Reference for languages (CEF; Council of Europe, 2001 & Little (2005)) and a certain cultural and constitutional knowledge as well, to be measured by additionally passing the CCSE exam. These exams, according to the law, are to be administered by Instituto Cervantes, the official Institute of Spanish language of the Government of Spain. This paper aims to study the repercussions and new effects the law is having on the Pakistan Instituto Cervantes Examination Center in terms of enrollments as well as the effects on a specific group of immigrants themselves; the immigrants from Pakistan.

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)0.036
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.355
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.338
Teacher spread0.324 · 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.

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of English LinguisticsSame topicSouth Asian Studies and ConflictsFrench-language works237,207