Bringing the Real World Into Developmental Science: A Commentary on Weber, Fernald, and Diop (2017)
Bibliographic record
Abstract
This article examines the parent intervention program evaluated by Weber et al. (2017) and argues that there are scientific and ethical problems with such intervention efforts in applied developmental science. Scientifically, these programs rely on data from a small and narrow sample of the world's population; assume the existence of fixed developmental pathways; and pit scientific knowledge against indigenous knowledge. The authors question the critical role of talk as solely providing the rich cognitive stimulation important to school success, and the critical role of primary caregivers as teachers of children's verbal competency. Ethically, these programs do not sufficiently explore how an intervention in one aspect of child care will affect the community's culturally organized patterns of child care.
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 | 0.024 | 0.081 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.019 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.050 | 0.084 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".