Preschoolers Are Sensitive to the Speaker’s Knowledge When Learning Proper Names
Bibliographic record
Abstract
Unobservable properties that are specific to individuals, such as their proper names, can only be known by people who are familiar with those individuals. Do young children utilize this "familiarity principle" when learning language? Experiment 1 tested whether forty-eight 2- to 4-year-old children were able to determine the referent of a proper name such as "Jessie" based on the knowledge that the speaker was familiar with one individual but unfamiliar with the other. Even 2-year-olds successfully identified Jessie as the individual with whom the speaker was familiar. Experiment 2 examined whether children appreciate this principle at a general level, as do adults, or whether this knowledge may be specific to certain word-learning situations. To test this, forty-eight 3- to 5-year-old children were given the converse of the task in Experiment 1--they were asked to determine the individual with whom the speaker was familiar based on the speaker's knowledge of an individual's proper name. Only 5-year-olds reliably succeeded at this task, suggesting that a general understanding of the familiarity principle is a relatively late developmental accomplishment.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".