Understanding Internal Exclusion: An Exploration of How Senior Leaders in Mainstream Secondary Schools Make Sense of Their Experience
Bibliographic record
Abstract
Internal exclusion (IE) describes the liminal physical or metaphorical space between a child's inclusion in mainstream class and exclusion from school. IE can be also known as “inclusion, learning support, exclusion, isolation, intervention or nurture groups” (Burton, Bartlett, & Anderson de Cuevas, 2009, p.151). Exploration of IE is limited to several studies (Gilmore, 2012; 2013; Gillies, 2016; Greenstein, 2014; Preece & Timmins, 2004). Taken together, these suggest that IE is constructed by staff and pupils as both support and sanction, and there is a significant diversity of approaches. In this study, I contribute to the critical Educational Psychology literature by taking a social constructionist and post-structuralist approach informed by the work of Foucault (1977/1991) to understand how senior leaders made sense of IE. I conducted unstructured interviews with a headteacher and assistant headteacher of two mainstream secondary schools in England at the start of the Autumn 2020 term, and analysed the data using a narrative approach (Riessman, 2008; Squire, 2013). Findings suggest that participants made sense of IE in relation to psychological discourses of behaviourism, humanism, and the psycho-medical, that were at times incongruent with one another. IE was identified as a technology that operationalised disciplinary power (Foucault, 1977/1991), yet it was subsumed into discourses of support for social, emotional and mental health (SEMH) needs. Risk to the core business of school was meaningful. These findings provide a valuable contribution to educational psychologists’ (EPs) understanding of IE and show how making these discourses visible enables them to be challenged. I conclude with practical implications for EPs, limitations, and recommendations for future research.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.011 | 0.018 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".