How Often and How Much?
Bibliographic record
Abstract
This article describes the current state of evidence regarding treatment intensity of print referencing intervention. Although studies of print referencing intervention demonstrate overall net positive impacts for children's emergent literacy development, researchers have yet to identify explicitly how often children should experience print referencing for these positive impacts to occur. Six print referencing intervention studies are identified in the literature and reviewed for differences in how often and how much print referencing intervention is delivered. Using the framework set out by S. F. Warren, M. E. Fey, and P. J. Yoder (2007), this article specifically discusses and compares variations in 5 treatment intensity variables (dose, dose form, dose frequency, total intervention duration, and cumulative intervention intensity) for the 6 studies of print referencing intervention. Effect-size estimates suggest a trend toward moderate effects of more intensive print referencing intervention and large effects for relatively less intensive print referencing intervention. This trend however is likely confounded by other contextual, individual, and treatment intensity factors. Therefore, suggestions for ongoing research exploring the differential effects of intensity of print referencing intervention are presented.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".