Linguistic Resources and "Ontologies" across Sense Modalities A Comparison between Color, Odor, and Noise and Sound - eScholarship
Bibliographic record
Abstract
Linguistic Resources and “ Ontologies ” across Sense Modalities A Comparison between Color, Odor, and Noise and Sound. Dubois Daniele ( daniele.dubois@inalf.cnrs.fr ) CNRS/LCPE, 44 rue de l’Amiral Mouchez, F-75014 Paris Cance Caroline (caroline.cance@ivry.cnrs.fr) Universite de Paris 3 & LCPE, 44 rue de l’Amiral Mouchez, F-75014 Paris After exploring categorization of color and other visual objects (Dubois, 1991; 1997), we have been recently investigating cognitive categories within other senses, such as olfaction and audition (Dubois, 1997b). We present here contrasted results concerning psychological representations of colors, odors, noises and sounds induced from their linguistic expression in (French) language. Quantitative evaluations of occurrences, their morphological, syntactic and semantic properties were computed on a corpus of 108 definitions produced by native speakers, according to previous analyses theoretically based in Dubois (2000; Dubois & Grinevald, 1999). Only partial results and conclusions will be reported here. Table 1: Number of nominal forms: Number of occurrences and number of single occurrences (Hapax) in the 4 corpora: odor color sound noise forms Occ. Hapax Among other indicators such as the number of verbs, relative clauses, adjectival forms (simple or deverbal ('pleasant') or denominal ('noisy') constructions), the nominal forms reveal that French linguistic resources vary across sense modalities : acoustic representations show less productivity and more agreement between subjects than colors and than odors. Table 2: Linguistic marks of “objectivity” and personal involvement (Percentage of subjects producing the word “something” and personal pronouns in their definitions) odor sound noise color “something” personal pronouns The lack of commonly shared naming for odors and acoustic phenomena correlates with the uncertainty of their definitions, stated as “something” that affects the subject, as reflected in the greater personal involvement for odor than for sound and noise, and lesser for color definitions. Conclusion Colors as visual objects seem to be processed as stimuli “standing out there”, whereas odors are more likely to be structured as effects of the world on the subject, therefore less autonomous from the experiential context. Acoustics phenomena can be represented at different degrees of “subjectivity” (or objectivity), contrasting noises that are more subjective than sounds, these latter referring to a more expert, objective, technical and scientific knowledge. If we always perceive “something”, through the diversity of senses, language diversely objectivizes and “stabilizes” our cognitive representations of the world into a large variety of linguistic forms. These forms may constrain the “ontology” given to the entities and lead to different distances between the “subject” and the “objects” of the world, from complex phrasing expressing the effects of the world on the subject, to simple “ basic ” names, which suggest the idea that things are “crying out to be named”. References Cance, C. (2000) Definitions d’objets sensoriels en langue francaise : odeurs, couleurs, bruits et sons. DEA de sciences cognitives, Universite de Lyon 2. Dubois D. (Ed) (1991). Semantique et Cognition. Paris: Ed. du CNRS. Dubois, D. (1997). Cultural beliefs as non-trivial constraints on categorization: evidence from colors and odors. B.B.S,. 20, 2, 188. Dubois, D. (Ed.) (1997)b. Categories et cognition, de la perception au discours Paris : Kime. Dubois, D., & Grinevald, C. (1999) “Denominations of colors in practices”, XXVI LACUS forum proceedings, (Edmonton, 1999), pp. 237-246. Dubois, D. (2000) Categories as acts of meaning, Cognitive Science Quartely, 1, 35-68.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".