Introduction to the special issue on SysMus16.
Bibliographic record
Abstract
SysMus16, the 9th International Conference of Students of Systematic Musicology, was held at the University of Jyvaskyla in June of 2016. SysMus came to Jyvaskyla on a rather short notice, a bit like a surprise guest. It had chosen us, so to say. Nevertheless, we were enthusiastic about the chance to host SysMus and welcome young, motivated scholars from around the world to our little town high up in the North. After the first SysMus in 2008 in Graz, Austria, the conference has traveled around Europe and Canada, with the 2016 meeting being the first SysMus held in the Nordic countries, which made us especially proud to host the meeting.SysMus is a conference series for students-mainly at master's and doctoral level-of research areas related to systematic musicology. Because SysMus promotes systematic musicology as an interdisciplinary field that aims to study music from computational, psychological, sociological, and other nontraditional perspectives, attendees bring wide and versatile backgrounds in fields such as music perception, cognition and psychology, music information retrieval, music sociology, ethnomusicology, music education, and music therapy. SysMus gives young academics the opportunity to meet, present, and discuss their work with their peers and to participate in an international scientific event.More than 100 participants from 13 countries attended SysMus16, attending 50 oral and poster presentations. Besides delegate presentations, three distinguished senior colleagues, Prof. Mari Tervaniemi from the University of Helsinki, Finland (who has provided a summary of her keynote for this Special Issue), Prof. Justin London from Carleton College, United States, and Prof. Ralph Spintge from the University of Music and Drama, Hamburg, Germany, were invited to give keynote speeches on aspects of music perception, cognition, neuroscience, therapy, and medicine. Furthermore, members of the host department gave hands-on workshops on equipment, tools, and techniques developed and practiced at the institution, including motion capture, music information retrieval, heart-rate variability tools, vibroacoustic therapy, and active music therapy.Not only is SysMus a forum for young scholars to experience being at a conference, it also gives young scholars the opportunity to organize a conference. The organizing committee of SysMus16 consisted of 10 bachelor's, master's, and doctoral students from seven different countries and four senior members from the Jyvaskyla Music Department. Students participated in all the necessary steps, from making a budget and applying for funding to creating the scientific and social program attending to all the necessary details.SysMus16 is the first to present a Special Issue of selected conference papers. This special issue reflects the diversity of the presentations at the conference including papers on music perception, music psychology, music and movement, music education, and music therapy. …
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.328 | 0.227 |
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".