A Different Tenor: Songs of Love and Sorrow—Re-Engaging the Social Ethics of Music
Bibliographic record
Abstract
Abstract: The question of how music relates to our existence as ethical beings has not always elicited the same response. For much of the twentieth century, the relation between music and ethics was addressed from the angle of music's autonomy. Music was fenced off from society so that it might better fulfill its own internal demands. Thus, in answer to the question whether music has, or should have, an ethical dimension, the predominating philosophical answer of the twentieth century was solidly negative. The article that follows, a response to this negative point of view, reproduces a panel discussion that took place in April 2010 during a conference entitled “Songs of Love and Sorrow: Re-Engaging the Social Ethics of Music.” Co-organized by the Institute for Christian Studies, the Toronto School of Theology, and the Royal Conservatory of Music, the conference attempted to bring to the musical arts a concern to re-evaluate the social significance of artistic experience and practice. Though not argued like an essay, the article highlights significant themes about the relationship of music to ethics, including the innately social character of music, its possible effect on our behaviour, the potential social content of sound itself, the positive social effect of music's ambiguity, the need to break down the barriers between music practitioners and interpreters, the role communities might play in sponsoring the work of musicians, and the possible compatibility between music's formal requirements and its potential for social engagement.
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.
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 | 0.012 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.048 |
| Scholarly communication | 0.015 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.010 |
| 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".