Underused Methods in Developmental Science to Inform Policy and Practice
Bibliographic record
Abstract
Abstract In this article, we offer recommendations for underused innovations and advances in research methods to enhance the quality of developmental science research. We couch our recommendations in terms of measurement innovations, design innovations, and analytic advances. We discuss six methods—the visual analog scale, the retrospective pretest–posttest design, appropriate timing and units of change, the accelerated longitudinal design, missing data treatments, and integrative data analysis. We conclude by encouraging developmental scientists to continue to incorporate advances and innovations in methods as they address the essential questions surrounding our goal to understand and improve the human condition across the life span.
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 | 0.799 | 0.838 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.007 | 0.075 |
| Scholarly communication | 0.034 | 0.054 |
| Open science | 0.013 | 0.025 |
| Research integrity | 0.017 | 0.055 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".