The Effects of Familiarity and Typicality on Naming Objects and Faces.
Bibliographic record
Abstract
It is found that when we name an object or a face, we often use basic level name (e.g., dog) rather than a nameat superordinate level (e.g., animal) or subordinate level (e.g., Labrador). In addition, although abundant evidence generallysuggested that both familiarity and typicality influence object recognition, how each of the two factors involves categorizationin terms of naming is not fully investigated yet. The present studies were performed to examine the familiarity and typicalityeffects on naming either an object or a face. Names for basic, superordinate, and subordinate levels were prepared for testingthe speed and correctness of object/face identification. As a result, familiarity, not typicality, induced a down-shift pattern fornaming. In contrast, typicality led to overall faster responses. The findings of the study indicated that familiarity and typicalityhave dissimilar effects on categorization by naming.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".