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Record W4399429034 · doi:10.5206/eei.v34i1.16826

“We Need Structures in Place”: Educators’ Experiences With Special Education at International Schools

2024· article· en· W4399429034 on OpenAlexaffvenue
Rebecca Stroud

Bibliographic record

VenueExceptionality Education International · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsQueen's University
Fundersnot available
KeywordsExpatriatePedagogyExploratory researchContext (archaeology)Qualitative researchAcculturationCollegialitySociologyPsychologyPolitical scienceEthnic groupSocial science

Abstract

fetched live from OpenAlex

This article engages the construct of the policyscape to explore how educators have experienced policy-to-practice dissonances when working at international schools overseas. Extracted from a qualitative study of educator acculturation in the context of the lived experiences of 17 kindergarten–Grade 12 expatriate teachers, counsellors, and school leaders at international schools in five regions in Southeast and East Asia, this subset of findings explores the most prevalent policyscape manifestations that emerged in the study. These manifestations involve issues about supporting students with known or probable “special education” needs. Findings include widespread perceptions by the participants of inadequate policy and program infrastructure to properly support students with special needs. These inadequacies ranged from identification processes, school and staff capacity, and leadership gaps, and they were further mired by ideological and cultural differences noted by stakeholder groups. Participants with local cultural mentors experienced greater self-efficacy and leadership capacity in addressing the policyscape manifestations. The study was exploratory, with the findings informing a research agenda to further investigate some of the gaps that emerged in the findings.

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 categoriesInsufficient 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 score0.319
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.001

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 head0.019
GPT teacher head0.373
Teacher spread0.354 · 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".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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