The Role of Teachers in the Organization of Inclusive Education of Primary School Pupils
Bibliographic record
Abstract
The article highlights the models of inclusive education of Italy, Germany, Sweden, Norway, and Great Britain. Inclusion models can be classified into three basic ones, according to the ratio of the number of primary school-aged children at general and specialized schools, namely: full inclusion, partial inclusion with a predominance of pupils at general schools, partial inclusion with a predominance of pupils at specialized schools. Full inclusion is present in Italy and Norway, partial inclusion with a predominance of students at specialized schools is observed in Sweden (88.40%), partial inclusion with a predominance of students at general schools is present in Germany and the UK.Models of inclusion differ on the following aspects: legal regulation, funding and amounts of financing for teachers’ trainings, initial and ongoing teachers’ training, an approach to the organization of inclusive education (partnership, peer-to-peer approach, centralized, decentralized), the practice of exchanging experiences of inclusion’s organization within the country, the ratio of the number of primary school-aged children at general and specialized schools. The factors specified determine the role of teachers in the organization of inclusive education of primary school pupils. In countries, support and assistance of teachers is provided at different institutional levels: in Germany – through the center for psychological and pedagogical support, inclusion support services; in Great Britain – by assistants; in Italy – by consultants, healthcare service professionals; in Sweden – through resource centers; in Norway – through state centers. Support of teachers’ professional development throughout life and teachers’ financial motivation have been introduced in the countries; thus, these measures have a positive effect on the integration of primary school pupils in the society.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".