Regulating the child in early childhood education: The paradox of inclusion
Bibliographic record
Abstract
This article contributes to the literature in critical special education by examining the perspectives of early childhood educators on inclusion and inclusive education. Six early childhood educators were interviewed, and the interview transcripts were analyzed using thematic analysis informed by Derridean deconstruction. Themes were identified across the interviews regarding the roles and relationships between educators, families, and children labeled with disabilities. These themes were clustered to form four overarching meta-themes highlighting axiomatic assumptions regarding expectations for inclusion: acceptance as advocacy, conformity as agency, othering as vulnerability, and knowledge as expertise. These meta-themes describe, in part, the regulatory practices that operate under the guise of “inclusion” in early childhood education to “normalize” children deemed to have deficits. To counter regulatory practices, we introduce the notion of relational inclusion as a generative, yet not unproblematic, alternative for reconceptualising the participation of learners. One goal of relational inclusion is to expand conventional notions of inclusion in ways that enable all children to participate and contribute to the culture of the classroom.
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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 | 0.014 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.083 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| 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".