Ethnic mobilities and representations in Rose-Marie on stage and screen
Bibliographic record
Abstract
This article interrogates representations of ethnicity in the long-lived musical play Rose-Marie from 1924, with music by Rudolf Friml and Herbert Stothart, book by Otto Harbach, and lyrics by Harbach and Oscar Hammerstein II, and its subsequent MGM film adaptations in 1936 and 1954. The story is set in Canada, and images of Indigenous people include white-created tropes of children of nature, vicious savages and drunkards. These views are manifested aurally through Indianist musical tropes of the time, and are especially evident in ‘Indian Love Call’ and ‘Totem-Tom-Tom’. Whiteness is performed opposite portrayals of Indigenous people that range from the ‘noble savage’ of the famous ‘Indian Love Call’ to Wanda, a First Nations woman characterized as violent and over-sexualized in the 1924 and 1954 versions. Friml’s multifarious score includes recognizable Indianist tropes of the time as well as quintessential operetta and musical comedy fare, thus musicalizing cultural differences through established Eurocentric means. In Rose-Marie , the title character’s mobile ethnicity shifts from being presumably French-born French Canadian in the original to English Canadian in the 1936 film (starring Jeanette MacDonald) and French Canadian in the 1954 version (starring Ann Blyth). Although Rose-Marie and Wanda behave in similar ways, Rose-Marie’s singing whiteness allows her to become a romantic lead, whereas Wanda, whose dance-dominated performance mode emphasizes a sensual physicality, is vilified because of her ethnic heritage.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".