Children’s and Adults’ Understanding of Proper Namable Things
Bibliographic record
Abstract
In two studies, we explored 5-year-olds’ and adults’ beliefs about entities that receive reference by proper names. In Study 1 we used two tasks: (1) a listing task in which participants stated what things in the world can and cannot receive proper names, and (2) an explanation task in which they explained why some things merit proper names. Children’s lists of proper namable things were more centred than adults’ on living animate entities and their surrogates (e.g., dolls and stuffed animals). Both children’s and adults’ lists of non-namable things contained a predominance of artefacts. Both age groups offered similar explanations for proper namability, the most common of which pertained to the desire or need to identify objects as individuals (or to distinguish them from other objects). In Study 2 we replicated the main results of the Study 1 listing task, using a modified set of instructions. The findings establish a set of norms about the scope and coherence of children’s and adults’ concept of a proper namable entity, and they place constraints on an account of how children learn proper names (Macnamara, 1982, 1986).
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".