Embedded Validity Scales to Examine Caregiver Response Styles When Measuring Infant/Toddler Developmental Status
Bibliographic record
Abstract
Validity of caregiver response to a developmental screening instrument was examined in 571 caregivers (51.7% identifying as ethnic minority) of infants/toddlers (48% female) assessed longitudinally from birth to 18 months. Three embedded validity scales were designed to detect: atypical (ATP), negative (NRS), and positive (PRS) response styles. Rates of responding on the ATP, NRS, and PRS scales relative to established validity measures, temporal stability including test-retest reliability of the scales, and relations between response styles and maternal education were examined. Response bias was low; however, significant differences due to maternal education were evident. More variable scores (ATP) and more advanced development (PRS) was consistently reported by caregivers with lower education. Caregivers with higher education reported their infants' development as less advanced (NRS). Base rates of uncommon responding ranged from 11.6% to 14.4% and 5.8% to 9.1% at liberal and conservative cut scores. Preliminary analysis of additional social-contextual sources of variation (e.g., caregiver mental health) in response styles suggests the need for complex modeling of multiple sources of bias in caregiver-reported developmental outcomes. These are the first embedded validity scales to be designed within a caregiver-reported instrument of infant/toddler development.
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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 | 0.018 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".