Creative Processes in the Shaping of a Musical Interpretation: A Study of Nine Professional Musicians
Bibliographic record
Abstract
Various studies have been conducted to understand the role of mental representation when musicians practice or perform music (Lehman & Ericsson, 1997; Sloboda, 2005) and the work steps required for a musician to prepare a concert (Chaffin et al., 2003). More recent studies examine creativity in the shaping of a musical interpretation (Barros et al., 2017; Lisboa et al., 2011; Payne, 2016; Wise et al., 2017). However, none of these studies answers the following questions: Why do expert musicians working from the same score create different musical interpretations? During individual practice sessions, what happens that allows each musician to produce significantly different interpretive results? To answer these questions, we instructed nine expert musicians to record their individual practice sessions, verbalize their actions and thoughts, and answer a self-reflection questionnaire. A third-party observer also described what happened during the practice sessions. We conducted interviews in order to gather additional information about the contents of the individual practice sessions; the musicians’ usual work habits; and their beliefs, values, and ideas regarding the role of the musician in the creative process. Based on the methodology of Analyse par théorisation ancrée (Paillé, 1994), we were able to take into account a diverse data set and identify aspects of the creative process that were specific to each individual as well as elements that all musicians shared. We found that the context in which the creative process takes place—the musician (e.g., his or her values and knowledge); the musical work (e.g., style, technical aspects, etc.); and the external constraints (e.g., deadlines, public expectations, etc.)—impacted the strategies used. The participants used reflection, extramusical supports, emotions, body reactions, intuition, and other tools to generate new musical ideas and evaluate the accuracy of their musical interpretations. We identified elements related to those already discussed in the literature, including the creative process as an alternation between divergent and convergent thinking (Guilford, 1950), creative associations (Lubart, 2015), and artistic appropriation (Héroux, 2016; Héroux & Fortier, 2014).
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".