Bibliographic record
Abstract
The development of mental representation in infants is controversial first of all for methodological reasons. Piaget's methodology focused on revealing the infant's developing knowledge as functional adaptation, demonstrable in action. He preferred to rely on unambiguous criteria for making inferences about the infant's underlying understanding. For example, intentional, goal-directed behavior was assumed only if the infant removed an obstacle to reach a goal. It is not that Piaget considered intentional behavior to be absent before the age that infants are capable of this action (about 9 months) but that it is not clearly demonstrable. Nativist infant researchers insist that methods requiring such actions on the part of infants preclude the discovery of sophisticated knowledge in very young infants who cannot yet perform the criterial actions. They claim, in fact, that the frontal cortex of young infants may not yet be mature enough to allow the sequencing of two actions, such as the removal of an obstacle to reach a goal (Diamond, 1991). These researchers adopt, instead, passive methods in which very young infants demonstrate their underlying knowledge by preferential looking at one stimulus longer than another. The challenge of this methodology is to design stimulus situations that can elicit looking responses related unambiguously to differences in stimuli. Evidence from Preferential-Looking Paradigms Spelke and her associates (Spelke, 1991; Spelke, Breinlinger, Macomber, & Jacobson, 1992) presented a series of situations to very young infants (aged 2 to 4 months) to test their representational knowledge of objects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".