Quality Early Childhood Education the Need for Special Education Services: A Symposium
Bibliographic record
Abstract
As the early childhood education field extends into providing more integrated school-based services, the time is right to examine the interconnections and opportunities evident in the provision of quality early childhood education services. As researchers, we were interested in examining whether the provision of quality early childhood education services mediates the need for special education services for children with identified exceptionalities. This symposium will address 8 papers related to this purpose: 1) the role of research in informing public policy; 2) early childhood education and special education; 3) parents perspectives on co-constructed pedagogical documentation in early learning settings; 4) the impact of full-day kindergarten on learning outcomes and self-regulation among kindergarten children at risk for placement in special education; 5) the impact of quality learning programs on the demand for student support services; 6) the benefits of including children with identified exceptionalities in quality early learning programs; 7) the importance of early intervention for children with autism spectrum disorder; and 8) the impact of quality early learning on students’ mental health. This symposium will provide opportunity for interactive discussion surrounding the literature review and findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".