Bibliographic record
Abstract
In this book, I have compared directly the evidence available on nonhuman primates and human infants/children with regard to several precursors of language: prelinguistic vocalizations, sound–meaning correspondences, communicative gestures, symbolic gestures and symbolic play, tool use and object permanence, representation, and memory. I think that this comparison has made it clear that the great apes differ very little from human infants in many communicative gestures, in tool use and object concept, in delayed imitation, and in the mental representation implied by their advanced abilities in these domains. Nonhuman primates can also be said to exhibit the necessary frequency modulation for prosody, as well as turn taking in dialogues. Where human infants depart from nonhuman primates is in their vocalization ability after age 4 months and particularly after the onset of CB containing true consonants in babbling is important not only for early word acquisition but also for later sentence production. Unlike nonhuman primates in the wild, human infants also show object sharing gestures that are related to early vocabulary acquisition and information-sharing gestures that are related to later word comprehension. A decrease in primitive gestures, such as protest and reach-request, also has longterm implications for later communicative competence and productive language complexity. Human infants also exceed apes in their ability to map sounds onto many different situations, and they exhibit invented symbolic gestures and complex symbolic play not found in apes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.139 | 0.110 |
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".