Aesthetic Systems Theory: Doing Hip Hop Kulture Research Together at Cipher5
Bibliographic record
Abstract
Aesthetic Systems is an original theory to explain how aesthetic resources are made, shared and used in the formation of art works and of collective and individual subjectivities. Aesthetic systems theory has ontological, epistemological and methodological implications for the study of aesthetics, aesthetics education and the cultural studies of music, and argues for community-engaged aesthetics research. The most striking implication of aesthetic systems is the methodological requirement to undertake community-engaged critical dialogical research informed by critical pedagogy, ethnomusicology and the cultural studies traditions. This article is both the story of the intellectual partnership that built Cipher5, an Edmonton-based hip hop research/study group and an argument for the necessity of community-engaged cartographies of mediation to shed light on the relationship between the formation of subjectivities and aesthetic education. If aesthetic systems form subjectivities, how might music education programs use this knowledge to inquire after the formation of student subjectivities?
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.021 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".