The sentiments, attitudes and concerns of educators when working under the conditions of inclusion
Bibliographic record
Abstract
This research is part of the international research project SACIE (Sentiments, Attitudes & Concerns about Inclusive Education). The international research team is formed of Dr. Ch. Forlin – Institute of Education Hong Kong, dr. T. Loreman and Dr. Ch. Earle – Concordia University College of Alberta, Canada, Dr. U. Sharma, Monash University, Victoria, Australia, and the author of this article. The research was focused on the field of sentiments, attitudes and concerns of educators when working with people with intellectual disabilities. This study aimed at discovering whether the above stated parameters change after qualification was achieved in special education. The results of research, encompassing a period of three years, aimed at describing a group of 794 educators from a developmental perspective of their attitudes, opinions and concerns focused on the process of inclusion. The research was divided into two phases – the 1st phase before commencement of the university (Bachelor’s) specialized study of special needs education, and the 2nd phase conducted a month before termination of this three-year study programme.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".