The gap between research and practice revisited: Accommodation practices amid the COVID-19 pandemic and beyond
Bibliographic record
Abstract
Previous research suggests that there is a demonstrated need to provide instructional and assessment accommodations for students with special needs in Canada and worldwide. Therefore, we conducted nine semi-structured interviews to better understand how Canadian elementary special education teachers’ perceived understanding of accommodations affected their practices before the COVID-19 pandemic, during school closures, and after school reopened in the province of Saskatchewan. Our interview data show that teachers’ perceptions of accommodations did not align with research and theory. Elementary teachers tended to utilize groupwise strategies for students with special needs. Overall, teachers’ perceptions and practices of accommodations remained constant prior to school closures and after school reopened, excepting some practices that were changed due to the COVID-19 safety protocols.
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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 | 0.119 | 0.097 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.019 | 0.060 |
| Scholarly communication | 0.020 | 0.017 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".