Two Left Feet: A Study of Multispecies Musicality in British Women's Sport
Bibliographic record
Abstract
The division between the study of human cultures, human minds, and animal behaviours and biology in academic scholarship exacerbates the assumption that music is exclusively human and that the human is singularly musical. In an attempt to avoid this simplified linkage between human music cultures and human biology, my research explores the interrelationship between (a) the “music-like” socialities underpinning sustained interspecies encounters, and (b) the human constructions of musicality (or unmusicality) that generate social allegiances and facilitate the strategic navigation of hierarchical power structures within multispecies environments. My dissertation examines two interspecies sports in the UK—equine freestyle dressage and canine heelwork to music—in which horses and dogs are trained predominantly by women to perform skills on command to the accompaniment of a music track. Drawing together perspectives on the animal from continental philosophy, ethology, gender studies, and critical theory, this multi-sited, multispecies ethnography aims to rethink the category of music through the animal and, conversely, the category of the animal through music. My argument is that the social bonds generated amongst freestyle dressage and heelwork to music’s sportswomen at shows are related to the interactions negotiated between the women and their horses/dogs during training and competition, both of which emerge from the interspecies performers’ music-like “expressions of desire” mediated sonically, visually, and tactilely between individuals through time. However, in order to engender these social bonds of community across human spectators as well as navigate the hierarchies of difference that govern their lives as mostly white, British, middle-class women, riders and handlers must place conditions on their animal partners’ expressions of desire as part of their construction of horse and dog (un)musicalities in social discourse. This latter characteristic of musical sociality, I argue, appears to be exclusive to the human.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.024 | 0.012 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".