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Intercultural education

2012· other· en· W4230089334 on OpenAlexaboutno aff
Trevor Hay

Bibliographic record

VenueThe Wiley-Blackwell Encyclopedia of Globalization · 2012
Typeother
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismEthnic groupPolitical scienceImmigrationChinaSociologyEducational attainmentNormativeSocioeconomic statusPoliticsState (computer science)Multicultural educationCultural diversityEconomic JusticeEconomic growthDevelopment economicsPopulationGender studiesLaw

Abstract

fetched live from OpenAlex

Abstract Since the 1970s, the need to develop and implement social and educational policies of a “multicultural” nature has been recognized by educational policy‐makers in many societies with substantial migrant and ethnic minority populations. While the term multicultural – and its relationship with the idea of culture itself – has been vigorously debated, it has become clear that multiculturalism connotes a range of policies intended to manage harmonious coexistence of ethnic minorities within a “core‐value” socio‐political framework. This is intended as a normative basis for greater measures of social justice and educational attainment for minority populations who have been underrepresented in measures of educational attainment and access to socioeconomic services and benefits. In ethnically diverse societies as different as Australia, Canada, South Africa, India, and China, the term also refers to the existence of widely divergent distributions of ethnic and cultural groups, from heterogeneous urban populations, as in Australia and the United States, to largely homogeneous minority populations contained within provincial borders in a larger nation‐state, such as China.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.101
Threshold uncertainty score0.339

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0070.005
Open science0.0010.009
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.1010.018

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 head0.010
GPT teacher head0.299
Teacher spread0.289 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations103
Published2012
Admission routes1
Has abstractyes

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Same venueThe Wiley-Blackwell Encyclopedia of GlobalizationSame topicReligious Education and SchoolsFrench-language works237,207