Kids See Human Too: Adapting an Individual Differences Measure of Anthropomorphism for a Child Sample
Bibliographic record
Abstract
The study of anthropomorphism in adults has received considerable interest with the development of the Individual Differences in Anthropomorphism Questionnaire (IDAQ; Waytz, Cacioppo, & Epley, 2010). Anthropomorphism in children—its development, correlates, and consequences—is also of significant interest, yet a comparable measure does not exist. To fill this gap, we developed the IDAQ-Child Form (IDAQ-CF) and report on 2 studies. In Study 1A, adults (N = 304) were administered the IDAQ and IDAQ-CF to directly assess comparability between the measures. In Study 1B, an additional 350 adults were administered the IDAQ-CF to confirm that the new measure had the same underlying structure as the original IDAQ when the measures were not administered together. In Study 2, children (N = 90) in 3 age groups—5, 7, and 9 years old—were administered the IDAQ-CF and an Attribution Interview, which probed their conceptions of a robot and puppet. Results indicated the IDAQ-CF a) is comparable to the original IDAQ in adult (Studies 1A and 1B) and child (Study 2) samples, and b) predicts children’s tendency to attribute animate characteristics to inanimate entities (Study 2). This research provides strong evidence that the IDAQ-CF is an effective adaptation of the original IDAQ for use with children.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".