"Joint (Ad)Venture Music" - 25th EAS Conference in Salzburg, 19th to 22nd of April 2017 - Conference Report
Bibliographic record
Abstract
What does it mean to work in a team when teaching a music class?How can we foster the cooperation between teachers, disciplines and organisations in the field of music education?Questions like these can summarize some of the aspects addressed in the conference "Joint (Ad)venture Music -Networking as a Challenge for Music Teachers" in Salzburg from 19 th to 22 nd of April 2017.Already the opening ceremony in the grand concert hall "Solitär" of the Mozarteum Salzburg gave meaning to the topic of the 25 th conference of the European Association for Music in Schools (EAS), which was held together with the 6 th European ISME Regional Conference, in several perspectives: Musically, a joint (ad)venture between an ensemble of the tuba and the recorder class of the Mozarteum Salzburg accompanied the event.Socially, as the last part of the opening session, all delegates got entangled into a web of finest Austrian wool that split out over all of the about 300 participants from more than 20 nations.Diverse understandings of "networking" thus spun through the presentations of research and practice papers as well as workshops, symposia and the inspiring keynotes that gave the starting point for every conference day.Susan O'Neil from the Simon Fraser University in Burnaby, Canada, keyed networks in the sense of self-spun webs of musical meaning in her ethnographic approach to the musical lives of students: Enlarging Lucy Greens' approach of informal learning, she aspires to analyse the network of musical activities in which every student, every person, is entangled -very much like the woollen spider net from the opening ceremony could illustrate.In a very inspiring additional presentation later in the congress, she gave, together with Yaroslav Senyshyn, an example for a corresponding research project which aims for the reconstruction of participatory music-learning practices following the concept of reciprocal co-authorship inspired by R. G. Collingwood.A perspective of networks as communication between the "ages" in the sense of historical comparison was presented by Ulrich Leisinger, musicologist at the Salzburg Mozarteum Foundation: He presented results of a document analysis regarding the question how the children of Johann Sebastian Bach and Leopold Mozart had experienced music education and how they had learned to compose.Main results indicate the clear understanding of music as a craftsmanship at this time -going as far as that it should usually "not be taught to children before eight years of age" -and that the emphasis did not seem to be put on "right or wrong" but rather on "better or worse" ways to compose.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.178 | 0.067 |
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".