An effective method for building meaning vocabulary in primary grades.
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
Teaching vocabulary to primary grade children is essential. Previous studies of teaching vocabulary (word meanings) using story books in the primary grades reported gains of 20%-25% of word meanings taught. The present studies concern possible influences on word meaning acquisition during instruction (Study 1) and increasing the percentage and number of word meanings acquired (Study 2). Both studies were conducted in a working-class school with approximately 50% English-language learners. The regular classroom teachers worked with their whole classes in these studies. In Study 1, average gains of 12% of word meanings were obtained using repeated reading. Adding word explanations added a 10% gain for a total gain of 22%. Pretesting had no effect on gains. In Study 2, results showed learning of 41% of word meanings taught. At this rate of learning word meanings taught, it would be possible for children to learn 400 word meanings a year if 1,000 word meanings were taught. The feasibility of teaching vocabulary to primary grade children is discussed.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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