Bibliographic record
Abstract
The escalation of research in both the psychology of music and the psychology of aging has led to a natural convergence on a new shared domain, that of psychogeromusicology. The present Volume of Psychomusicology represents different views of this domain: melodic memory, rhythmic processes, neurophysiology, quality of life, strong musical experiences, adult development, music training, and ergonomics. An international perspective is represented by authors from France, Germany, Sweden, Japan, Canada, and the United States. Taken together the articles provide a foundation for further basic and applied research in this new area. The Volume also invites readers to consider the options and opportunities for lifelong involvement in music. Toshio Iritani, an Emeritus Professor of Psychology in Japan, began to study piano after the age of 60 years. Within five years, he performed Beethoven Sonatas, and Chopin Nocturnes and Etudes. The present author and guest editor of this Volume of Psychomusicology had a similar experience about a decade earlier in her life, when she began the study of singing. Within five years, she mastered some of the most challenging repertoire for the soprano voice and earned a credential in voice performance from the Royal Conservatory of Music. These and countless other examples - from the legendary performances of octogenarians like Pablo Casals or Arthur Rubinstein to the nonogenarian amateur choristers in Germany and elsewhere-serve to illustrate lifelong learning and enjoyment from music. Within psychomusicology, developmental psychology has directed much attention to the potential for music in infancy and early childhood (Deliege & Sloboda, 1996;Hargreaves, 1996). By comparison, the older end of the lifespan spectrum has been overlooked. The present Volume addresses this neglect. Interest in both the psychology of music and the psychology of aging has escalated independently in the last two decades. One common factor affecting the growth in both areas is the Cognitive Revolution. Its beginning is sometimes marked with the publication of the first book entitled Cognitive Psychology (Neisser, 1967), however, the cognitive Zeitgeist was motivated directly by technological developments of the 1950s. Newly invented computers had promised much for artificial intelligence, the ability for a machine to carry out human tasks like speech recognition and translation. These early promises were met by disappointment when computers failed to easily carry out these tasks. As psycholinguist George Miller (1974) pointed out, better theories of cognitive organization were needed as a basis for the design of computers that could take on these human tasks. The earliest history of experimental psychology had of course directed attention to cognitive issues concerning thought and mental imagery (including music). These pioneers of experimental psychology, however, did not have the necessary scientific methodologies needed for successfully obtaining and quantifying data. The Behaviorist period from 1920 to 1970 arose as a reaction to this failure. The Behaviorists ultimately developed the scientific rigor that could later serve the renewed focus on mind of the Cognitive Revolution. The renewed legitimacy of mind by the Cognitive Revolution opened the doors, admittedly slowly at first, to psychomusicology and also to information processing, memory, and thought, which are central to many studies of the psychology of aging. Technological developments in the audio industry also facilitated the study of music perception and cognition. The same technology that made it possible to control musical stimuli in the laboratory also increased the accessibility to music of the average individual, through home stereo systems, sound systems in vehicles, wearable devices (walkmen), and portable boom boxes. Amplification created instant amphitheatres on any summer hill or winter stadium. The generation most affected by developments in audio technology was initially a youth culture. …
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| 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".