An Embryonic Journey of Musical Entrepreneurship with “The Captain,” Jorma Kaukonen, and His Co-Pilot, Vanessa
Bibliographic record
Abstract
The music business is a case study in how macro-environmental factors can radically transform an industry. Developments such as digital production and distribution, coupled with social media, crowdfunding, and changing consumer preferences, have dramatically transformed the business model for the recorded music industry in recent years and spurred the development of entrepreneurial business models to enable musicians to survive in their changing environment. As a solo artist and founding member of the musical groups Jefferson Airplane and Hot Tuna, Rock and Roll Hall of Fame musician Jorma (“The Captain”) Kaukonen has recorded albums for major labels such as RCA, Sony, and Columbia, as well as independent labels such as Relix and Red House Records. In this interview, Jorma and his wife and business manager, Vanessa Kaukonen, discuss their experiences as musical entrepreneurs in the digital age, including their founding of the unique Fur Peace Ranch guitar camp in the hills of Appalachia. The entrepreneurial business undertakings of the Kaukonens highlight the potential for entrepreneurial musicians to develop innovative and sustainable business models for surviving in this new world of music.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.016 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".