What 2 Listen 2: Reinventing the Presence of Tastemaker Influences in Music Discovery Through User Interaction and Aggregate Data
Bibliographic record
Abstract
Historically, the process of music discovery has been fostered through the personal connection(s) listeners develop with music and artists via broadcast media formats. Streaming technology has made music more accessible to the listener than ever before, but it has also failed the listener, inhibiting the process of music discovery by eliminating the tastemaker. By referencing the theory of Public and Counter-publics by Robert Warner, the paper outlines importance of audience recognition, response, and personal connection to music discovery. In 1942 Joseph Schumpeter wrote about “incessant product and process innovation”, coined the phrase “creative destruction” (a process through which something new brings about the demise of whatever existed before it) and proclaimed it to be “the essential fact about capitalism”. Despite this, Schumpeter also outlined the concept of “creative response” (innovative acts by entrepreneurs) and its importance to society. What 2 Listen 2 embraces the ideology of Schumpeter and creates a multi-level solution to expand the role of the tastemaker, and restore the concept of personal connection to the process of music discovery via storytelling. This solution has been articulated as a market ready broadcast property as well as an app/web solution in a beta form.
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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 | 0.015 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.015 | 0.020 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| 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".