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Record W2887075945

The Figured World of Diversity: Korean Preschool Teachers` Beliefs About Multicultural Education

2016· article· en· W2887075945 on OpenAlexvenueno aff
Min Jung Lim, Jinhee Kim

Bibliographic record

VenueEarly childhood education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismMulticultural educationDiversity (politics)Context (archaeology)PedagogyCultural diversityEarly childhood educationEthnic groupPsychologySociologyTeacher educationQualitative researchSolidaritySocial sciencePolitical scienceAnthropologyGeography
DOInot available

Abstract

fetched live from OpenAlex

This study examined Korean preschool teachers` beliefs about multicultural education by utilizing the concept of “figured worlds” (Holland, Lachicotte, Skinner, & Cain, 1998). Drawing on a qualitative study of a multicultural education course, we explored the perspectives and experiences of preschool teachers within a particular cultural context. For data analysis, we collected different course assignments during one semester and conducted individual interviews. We found that the preschool teachers brought the deficit discourse of diversity, which was reflected in public discourse on multicultural education, to the course. We also found that the critical inquiry-based course helped the preschool teachers to recognize their own figured worlds of diversity. The preschool teachers viewed diversity according to the master figured world of ethnic solidarity, which has double-sided influence on their multicultural teaching. This study discussed how teacher education programs can support early childhood teachers to be critical multicultural educators.

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)0.004
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.008
Scholarly communication0.0050.005
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.284
Teacher spread0.271 · 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 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
Published2016
Admission routes1
Has abstractyes

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