In their own terms, on their own terms: Capturing meaning in community musical theatre cast member e-journals
Bibliographic record
Abstract
Abstract Community musical theatre actively engages individuals in music-making and dramatic performances across the United States. Through these productions, enthusiastic volunteers are afforded socially and musically meaningful opportunities to perform alongside other members of their community. While a large body of scholarly musicological and historical literature on American musical theatre exists, little work has been done to engage individuals involved in these community productions in an attempt to understand reasons for participation or to examine the meaning found in participation. In response to this gap in the literature, this article reports research from an intensive ethnographic study of a Florida community group as they present a production of Maury Yeston’s blockbuster musical Titanic. In addition to ethnographic observation and interviews, e-mail-based cast member journals (e-journals) were used as a way to explore participants’ experiences as the show progressed. E-journal entries are the focus of this article, discussed here in terms of the meaning they capture and the general utility of the methodology. Consideration is given both to the results of this data collection process in the present ethnography and to the usefulness of this approach for future research.
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 | 0.013 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.014 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".