Parent-Infant Interaction Tasks Adapted for Remote Testing: Strengths, Challenges, and Recommendations
Bibliographic record
Abstract
<p>The closure of in-person laboratories and decreased safety of face-to-face interactions resulting from the COVID-19 pandemic jeopardized the ability of many developmental researchers to continue data collection during this time. Disruptions in data collection are particularly damaging to longitudinal studies, in which the testing of different age groups occurs on a continuous basis, and data loss at one time point can have cascading effects across subsequent time points and threaten the viability of the study. In an effort to continue collecting data for a longitudinal study on emotion development started in-person pre-pandemic, we adapted two parent-infant interaction tasks (free-play task and toy removal task) for a remote testing framework. Our procedure for pivoting these tasks to a supervised, remote online testing framework is outlined and the associated strengths and challenges of testing in this format (e.g., feasibility and implementation, testing environment and task setup validity, and accessibility, recruitment, and diversity) are critically evaluated. Considerations for applying this framework to other behavioral tasks are discussed and recommendations are provided.</p>
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".