Call for Non-Verbal Mind-Mindedness Measures for Use in Infancy and Across Cultures
Bibliographic record
Abstract
Abstract Maternal mind-mindedness, which examines mothers' representational capacity to treat their children as individuals with their own minds, has traditionally been operationalized by coding mothers' mental state comments to or about their children. Mind-mindedness has been studied predominantly in Western cultures, where it predicts children's social-cognitive developments. However, in many non-Western cultures, mothers do not readily talk about their children's mental states; they may use nonverbal behaviors to manifest their mind-mindedness. Nonverbal behaviors may also be the way mind-mindedness is conveyed to young infants. Theorists have been puzzled by the fact that mind-mindedness in mothers' speech prior to when infants understand language predicts infants' later social-cognitive developments. In this article, I call for mind-mindedness measures to include nonverbal behaviors. Such measures may reveal behaviors involved in communicating mind-mindedness to infants and provide an avenue to equitable investigations of mind-mindedness in diverse cultures, thus advancing the theory and scope of the field.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".