Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hybrid artist-scientists are now fairly common. It wasn’t always thus. Certainly music has a relatively long history of cross-fertilization with science, not least because of its obvious mathematical qualities, but also because of the medium-term relationship between music and technology. In formal music studies though, the medium of music was generally considered indivisible from itself, even as mathematical models were used to justify certain theories. Film also has a similar, if somewhat less precisely formalized history, as evidenced by the long history of montage film and visual music. Other fine arts have had less clear relationships with science. This can no longer be said to be the case. Artists are collaborating with biologists, computer scientists, geographers and researchers from other far-flung disciplines. Similarly scientists are learning the value that artists can bring to a project in terms of creativity and “ways of seeing” (Berger, 1972, 1). On-going discipline-centric resistance based on adherence to traditional barriers between the (subjective) arts and the (objective) sciences continues to be prevalent; however, it is fair to say that the gulf between art and science that has widened since the Enlightenment has now been widely challenged by a body of scholars, artists and scientists.©Journal of Professional Communication, all rights reserved.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it