MétaCan
Menu
Back to cohort
Record W4415774699 · doi:10.1080/13603116.2025.2546909

Against performativity: towards a comprehensive model for inclusive education

2025· article· en· W4415774699 on OpenAlex
Christopher Johnstone, Hayley Niad, Valerie L. Karr, Heather M. Aldersey

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Inclusive Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicEducational Theory and Curriculum Studies
Canadian institutionsQueen's University
FundersEgypt USAID
KeywordsInclusion (mineral)Higher educationMainstreamingQualitative researchSpecial educationField (mathematics)

Abstract

fetched live from OpenAlex

Inclusive education has become a generally accepted approach to promoting education for children with disabilities worldwide. Both global governance organisations and national governments have called for greater inclusivity in education systems. As such, implementing organisations have sought to demonstrate their programmes align with policy trends and often apply the term ‘inclusive’ to their educational programmes. In this article, we argue that some of these activities are performative and use inclusive terminology to describe activities that may only partially address inclusive outcomes. As an example, we draw upon data from United States Agency for International Development (USAID) programmes that conceptualised inclusion in three different ways. We reflect on lessons learned from these programmes and introduce the concept of ‘comprehensive’ inclusive education as a counterweight to performative inclusive education. We conclude by offering an array of practices and policies that may inform comprehensiveness for education programmes.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.020
GPT teacher head0.419
Teacher spread0.399 · 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