Short-term retention of popular music in older adults: Supports for a plasticity theory of implicit music knowledge acquisition
Bibliographic record
Abstract
Based on our Plasticity Theory of Implicit Music Knowledge Acquisition (PTIMKA), we tested the hypothesis that adolescence is a sensitive period for acquiring musical information, including a lifelong musical grammar. Older adults (N = 27, mean age = 65.7 years; SD = 6.7) identified artist, title, and year of popularity and rated their familiarity for short excerpts of 36 songs popular between 1962 and 2021. Knowledge and familiarity were greater for music popular during the participants’ adolescence. A subsequent surprise retention task required participants to choose which of 2 excerpts had been presented in the first task. For each of 36 trials, targets and foils represented the same era of popularity. Retention (dꞌ) and confidence in retention judgment were also stronger for the songs of adolescence, even though targets of all eras had just been presented in the previous 15 minutes. It is argued that popular music styles congruent with an adolescence-established grammar were more accurately encoded than styles violating this grammar, as would songs popular before or after adolescence. Prior data from younger adults showing trajectories opposite to those for older adults as a function of decade of popularity are further consistent with this interpretation and with PTIMKA.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".