Implementation of Arkansas’s Initiative to Reduce Suspension and Expulsion of Young Children
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article describes the development, initial implementation, and formative evaluation of Arkansas’s plan to reduce suspensions and expulsion from early care and education (ECE) settings. We describe how Arkansas used multifaceted implementation strategies to facilitate change in six areas: policy, workforce development, specialized supports, family partnerships, child screening, and data tracking. We also highlight key findings from the formative evaluation. For example, needs assessment data revealed that 40.8% of ECE providers suspended at least one child in the past year, and 9% expelled one or more children. We evaluated efforts to educate ECE providers on new nonexpulsion policies and new supports, and results indicate that 89.5% of directors agreed that they understand why young children should not be suspended or expelled, though the majority reported concern about implementing a nonexpulsion policy. Initial utilization data from a new ECE provider support system indicate that in the first quarter, 53 requests were submitted for help with challenging classroom behavior. Most requests involved male children over the age of 3, and one-third of the requests referenced traumatic events experienced by the children.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it