One Label or Two? Linguistic Influences on the Similarity Judgment of Objects between English and Japanese Speakers
Why this work is in the frame
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Bibliographic record
Abstract
Recent findings have re-examined the linguistic influence on cognition and perception, while identifying evidence that supports the Whorfian hypothesis. We examine how English and Japanese speakers perceive similarity of pairs of objects, by using two sets of stimuli: one in which two distinct linguistic categories apply to respective object images in English, but only one linguistic category applies in Japanese; and another in which two distinct linguistic categories apply to respective object images in Japanese, but only one applies in English. We conducted four studies and tested different groups of participants in each of them. In Study 1, we asked participants to name the two objects before engaging in the similarity judgment task. Here, we expected a strong linguistic effect. In Study 2, we asked participants to engage in the same task without naming, where we assumed that the condition is close enough to our daily visual information processing where language is not necessarily prompted. We further explored whether the language still influences the similarity perception by asking participants to engage in the same task basing on the visual similarity (Study 3) and the functional similarity (Study 4). The results overall indicated that English and Japanese speakers perceived the two objects to be more similar when they were in the same linguistic categories than when they were in different linguistic categories in their respective languages. Implications for research testing the Whorfian hypothesis and the requirement for methodological development beyond behavioral measures are discussed.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it