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Record W4390804453

Inmigración y pluralidad lingüística

2018· article· es· W4390804453 on OpenAlexaboutno aff
Elena Atienza Macías

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2018
Typearticle
Languagees
FieldSocial Sciences
TopicImmigration and Intercultural Education
Canadian institutionsnot available
Fundersnot available
KeywordsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

El fenómeno migratorio se ha convertido en una realidad de dimensión planetaria, característica visible de un proceso de globalización cada vez más acusado. España, no ha sido ajena a este fenómeno; convirtiéndose en una realidad multicultural en la que conviven personas de etnias, nacionalidades y culturas diversas. Esta diversidad cultural y étnica es un reto al que no se enfrenta sólo España, sino que es una tendencia que cobra cada vez mayor importancia en toda Europa. En este trabajo de investigación, se estudia especialmente la identidad lingüística como pieza clave para la configuración de un marco efectivo de los derechos humanos. Resulta de especial trascendencia el análisis del modelo seguido en un país, paradigma de la multiculturalidad: Canadá. De suerte que fue pionero en el mundo en proclamar de modo oficial, allá por 1971, su apuesta formal y decidida por el multiculturalismo como política de gestión pública de la diversidad cultural. Igualmente merece un análisis la construcción jurídica que ha ideado este país en torno al “acomodo razonable de derechos”, concepto novedoso y de indiscutible actualidad que, ha atraído la atención de Europa que, como sociedad plural, puede importar esta fórmula. Y no sólo de Europa, puesto la situación del entorno cultural y lingüístico de Quebec presenta un claro paralelismo con las situaciones que existen en algunas Comunidades Autónomas de España, siendo un modelo excelente para sociedades complejas como la vasca o la catalana, ambas sociedades plurales en el plano lingüístico.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0040.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0510.001

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 head0.288
GPT teacher head0.625
Teacher spread0.336 · 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 designNot applicable
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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