Influence of “indeterminate music” on visual art: a phenomenological, semiotic and fractal exploration
Bibliographic record
Abstract
Abstract Indeterminacy in music, a well known neo-avant-garde approach of composing sound where some features of a musical work are left open to chance or to the interpreter’s free choice, became noticeable among some American music composers such as John Cage, Earle Brown, Morton Feldman and Christian Wolff in the mid 20th century. Simultaneously, a group of artists from the West created “abstract expressionism” in visual arts, which showed a strong resemblance with this “indeterminate music”, both using two kinds of abstract languages. The commonality among these two art forms is the free improvisation of creative activity. The correspondence between the indeterminate music induced emotions and the depicted emotional contents in paintings is a relevant area which is still scientifically unexplored. To investigate the same, we conducted a case study where a visual artist listened to four music clips composed by the above mentioned musicians and created four paintings. The visual artist is strongly inspired by the abstract expressionist methods and these methods lend well to inspirational work based on listening to indeterminate music.To understand the nature of intermediality, if any, that exists between “indeterminate music” and “evoked abstraction” in paintings, the artist’s phenomenological interpretations of the process was compared with detailed semiotic analysis of specific musical and visual elements and the nature of their relatedness. Fractal analysis in the form of Detrended Fluctuation Analysis (DFA) was also done on both the acoustic waveforms of the chosen music clips and the corresponding paintings to explore possible correlations. Some unique findings yielded from the analysis, which hint toward strong correlation between the prominent musical features of indeterminate music and the prominent visual features of the paintings inspired by them. This novel study has the potential to offer both new methodology as well as better understanding the features of intermediality between “indeterminate music” and visual art.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.021 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".