Re-Imagining Inclusive Education for Young Children: A Kaleidoscope of Bourdieuian Theorisation
Bibliographic record
Abstract
This article discusses critical issues related to the development and practice of inclusive education of young children, from the perspective of Bourdieu’s conceptual lenses of habitus, capital and field. The target question is: How can Bourdieu’s lenses of critical social theory be applied to the development and implementation of early childhood inclusive education? Under this question, I situate early childhood inclusive education in four components (active learning environment, involvement, relationships and wellbeing), and critically analyse these in terms of Bourdieu’s three conceptual lenses. I argue that effective inclusive education of young children must not conform to modernist epistemology, which locates knowledge exclusively in teachers and that, Bourdieuian conceptual tools offer refreshing epistemological and reflective radars for re-imagining and enacting pedagogical practices that contribute to all children’s holistic development.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.074 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".