COVID-19 first lockdown as a window into language acquisition: associations between caregiver-child activities and vocabulary gains.
Bibliographic record
Abstract
The COVID-19 pandemic, and the resulting closure of daycare centers worldwide, led to unprecedented changes in children’s learning environments. This period of increased time at home with caregivers, with limited access to external sources (e.g., daycares) provides a unique opportunity to examine the associations between the caregiver-child activities and children’s language development. The vocabularies of 1742 children aged 8-36 months across 13 countries and 12 languages were evaluated at the beginning and end of the first lockdown period in their respective countries (from March to September 2020). Children who had less passive screen exposure and whose caregivers read more to them showed larger gains in vocabulary development during lockdown, after controlling for SES and other caregiver-child activities. Children also gained more words than expected (based on normative data) during lockdown; either caregivers were more aware of their child’s development, or vocabulary development benefited from intense caregiver-child interaction during lockdown or both. We discuss these results in the context of the extraordinary circumstances of the COVID-19 pandemic and highlight limitations of the study.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".