A Socio-Cultural Analysis of Practitioner Perspectives on Implementation of Evidence-Based Practice in Special Education
Bibliographic record
Abstract
Despite the central role “evidence-based practice” (EBP) plays in special education agendas for both research and policy, it is widely recognized that achieving implementation of EBPs remains an elusive goal. In an effort to better understand this problem, we interviewed special education practitioners in four school districts, inquiring about the role evidence and EBP played in their work. Our data suggest that practitioners’ responses to policies that press for increased use of EBP are mediated by a variety of factors, including their interpretations of the EBP construct itself, as well as the organizational conditions of their work, and their access to relevant knowledge and related tools to support implementation. We interpret these findings in terms of their implications for understanding the problem of implementation through a more contextual and ecological lens than has been reflected in much of the literature to date.
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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 | 0.088 | 0.103 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.014 | 0.029 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.003 | 0.006 |
| 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".