The development of conceptual colour categories in pre-school children: Influence of perceptual categorization
Bibliographic record
Abstract
This study investigates the influence of perceptual colour categorization on the development of conceptual colour space in 43 pre-school children as a function of language-age. Knowledge of the 11 basic colour terms identified by Berlin and Kay (1969) was assessed in comprehension and naming tasks. Children's ability to comprehend basic colour terms was assessed in a spoken word-to-colour matching task in which a target colour was presented with two distracters from either distant or adjacent perceptual colour categories. Children's ability to name basic colour sensations was measured in an explicit naming task. Results showed that children's comprehension of basic colour terms was influenced by the perceptual relationship between the target and distracter colours. Most importantly, at a language-age of 3 years and above, naming errors were more likely to be made to adjacent, rather than distant, perceptual colour categories. These results are consistent with the prediction that categorical colour perception influences the underlying structure of developing conceptual colour space during the period in which children acquire basic colour terms.
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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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".