Bibliographic record
Abstract
Abstract The paper deals with words that denote feelings rather than with feelings as such. It proposes the strictly lexicographic description of some names of ‘psyche-induced feelings1’ [= ‘feelings2’], such as joy or amazement, in contrast to the names of ‘body-induced feelings1’ [= ‘sensations’], such as hunger and tiredness. This description is based on the semantic prime ‘feel1’, which itself is explicated through a naïve model of the human psyche. Our theoretical and descriptive framework is the Explanatory Combinatorial Dictionary: its main principles, the notions of lexical unit (described by a lexical entry) and vocable (described by a lexical superentry), and the three major zones of a lexical entry. A tripartite general schema of the lexicographic definition of a feeling2 name is proposed: the central (= generic) component, the Stimulus component, and the Effect component. According to the Stimulus component, four major classes of feeling2 names are distinguished: names of reactions to facts, to thoughts, to beliefs, and to wishes. These classes are illustrated with the definitions of several English feeling2 names. A complete lexical entry for the feeling2 name anger(N)1 is given.
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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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".