Reconsidering the Role of Instrumental Technique in Creative Process: The ‘Canadian School of Double Bass’ Applied to Jazz Performance
Bibliographic record
Abstract
Contemporary research exploring embodiment in music has suggested that creative musical thought is directly linked to a performer’s learnt physical techniques. Within this discourse, it is understood that an improvising musician’s embodied physical techniques play a primary role in informing their creative processes. This view suggests that subsequent changes or developments to a jazz musician’s physical technique may fundamentally influence the ways in which musical ideas are conceived while improvising. This article begins by unpacking a cross-section of literature in support of this claim, before presenting the results of a practice-led autoethnographic experiment exploring the relationship between instrumental technique and creative practice. In this experiment, I transition to a new way of playing the double bass, informed by Joel Quarrington’s The Canadian School of Double Bass, and observe transformations in hand frame, use of vertical shifts, use of register, feelings of tension and overall dexterity, all of which appear to influence my creative decision making. The results highlight how this reformed technical approach affected the physical accessibility of certain intervallic options, and appear to have fundamentally impacted my conception and construction of melodic content on a cognitive level.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.038 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".