Emotional Fluctuations in Bob Dylan's Lyrics Measured by the Dictionary of Affect Accompany Events and Phases in his Life
Bibliographic record
Abstract
Lyrics for Bob Dylan's songs between 1962 and 2001 (close to 100,000 words) were scored with the help of the Dictionary of Affect in Language (Whissell, 2006). Means for Pleasantness, Activation, and Imagery are reported for 22 Blocks characterizing this time span. Significant but weak differences across Blocks were found for all three measures at the level of individual words. Emotional fluctuations in words included in Bob Dylan's lyrics accompanied events and phases in his life, although they were not entirely dictated by these events. Dylan used more highly Imaged and more Active words at times when his work was critically acclaimed. More Passive word choices characterized times of prolonged stress, and more Pleasant choices times of experimentation. Dylan's three popularity peaks were used to divide the singer's career into three stages (rhetor, poet, sage) which differed in terms of pronouns used.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".