GABRIELA ILIE AND WILLIAM FORDE THOMPSON University of Toronto USING A THREE-DIMENSIONAL MODEL of affect, we
Bibliographic record
Abstract
compared the affective consequences of manipulating intensity, rate, and pitch height in music and speech. Participants rated 64 music and 64 speech excerpts on valence (pleasant-unpleasant), energy arousal (awake-tired), and tension arousal (tense-relaxed). For music and speech, loud excerpts were judged as more pleasant, energetic, and tense than soft excerpts. Manipulations of rate had overlapping effects on music and speech. Fast music and speech were judged as having greater energy than slow music and speech. However, whereas fast speech was judged as less pleasant than slow speech, fast music was judged as having greater tension than slow music. Pitch height had opposite consequences for music and speech, with high-pitched speech but low-pitched music associated with higher ratings of valence (more pleasant). Interactive effects on judgments were also observed. We discuss similarities and differences between vocal and musical communication of affect, and the need to distinguish between two types of arousal: energy and tension.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".