Trends in Inclusive Education in the USA and Canada
Bibliographic record
Abstract
Abstract This paper deals with foreign experience of implementing inclusive education for children with special educational needs in the United States and Canada. Legal documents on inclusive education in foreign countries have been analyzed. The most relevant topic of American and Canadian scholars’ researches on reforming special education is related to integration, that is gradual transition from exclusion of children with special educational needs to inclusion in comprehensive schools. Based on the analysis of American and Canadian researches on inclusive education it has been concluded that the changes in legislation and education policies of North American countries aim to achieve the highest level of progress in regular education and special education. It has been found that the development of inclusive education in Canada has undergone and is significantly influenced by the American education system. However, unlike the United States, Canada does not have a single legislative act that would standardize the introduction of inclusive education in the country. Each province has autonomous educational documents that specify the requirements for the inclusive education organization. It has been specified that in American schools, effective educational technology in inclusive education is a team approach when effective partner relationships are formed. A key to the successful integration of a child with special educational needs is the development of an individual curriculum. The Canadian education system, having its own national peculiarities that predetermine the differences in the course of education reforms, has always supported the democratic movement for civil rights and anti-discriminatory attitudes in US education. Foreign law and inclusive practice are an important source of ideas about possible ways to solve the problems of implementing inclusive education in Ukraine.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.012 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".