Throwbacks that move us: The dance-inducing power of nostalgic songs
Bibliographic record
Abstract
The urge to move to music, often referred to as groove, is influenced by various factors, including familiarity with the music. The influence of nostalgia, which involves familiarity but also includes pleasant, sad, and wistful emotions, remains largely unexplored. Here we investigate the impact of both familiarity and nostalgia on the desire to tap, move, and dance along to music. To evoke nostalgia, we selected popular songs from the participants' adolescent years. More recent songs served as a low-nostalgia but familiar control. Participants completed an online experiment, rating songs based on their desire for three different movement types (tap, move, and dance), as well as enjoyment, familiarity, and nostalgia. Nostalgic songs elicited higher desire to move than familiar songs across all three movement categories. Additionally, both familiarity and nostalgia predicted move and tap ratings, but only nostalgia emerged as a predictor for dance ratings. Our results suggest a distinctive role for nostalgia, beyond the influence of familiarity, in motivating the desire to dance.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".