"An Airy Spirit": Developing Identity Through Music, Performance, and Perception
Bibliographic record
Abstract
How do audiences come to understand a character who appears to lack a discrete performed identity? This paper explores how, in performance, music and theories of magic and reader response interact to create the identity of the musical spirit, Ariel, from William Shakespeare’s (1564-1616) The Tempest (1611). To facilitate this exploration, I outline Ariel’s characterisation across six productions from the Renaissance, Restoration, and modern-day on two levels: textual (concerning how culturally-bound theories of magic and gender affect interpretations of the play’s script), and performed (concerning practical decisions such gender casting, voice type, and visual design). Across both the textual and performed levels, I emphasise the roles of socio-cultural contexts and resultant audience perceptions in informing Ariel’s identity in each production, ultimately proposing that while Ariel’s textual identity as a genderless spirit remains relatively stable from the Renaissance to the modern-day, each production of The Tempest creates a new performed identity for the character through dynamic interactions between culture, history, directors, performers, and audiences.
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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.028 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".