Snyder and Berlin’s “coon song” That Opera Rag is a strong case study for examining the complex attitudes towards class, race, nationality, and gender in the early 1900s. That Opera Rag, despite its many conventional features, has three which defy expectations: a mediant relationship between the two tonal areas of A minor and F major, operatic (as well as popular) quotations, and irregular phrase lengths resulting from the opera quotations. This song perhaps began as an instrumental example of “ragging the classics” by combining highbrow operatic music with lowbrow ragtime conventions, and can be heard as a spoof of operatic grandeur. The lyrics, which utilize minstrelsy misspellings, “humorously” portray black housepainter Sam Johnson as an opera neophyte who misidentifies the quotations. Johnson’s recognition of operatic music represents a contemporary fear for white Americans that African Americans were asserting cultural aspirations through the appreciation of opera. Yet That Opera Rag was also used in the Broadway play Getting a Polish, in which a (white) Montana widow tries to transcend her “common” status by seeking refinement in Paris. May Irwin, the star of Getting a Polish, used That Opera Rag as an unconventional vehicle to stardom by performing these racist songs in a masculine fashion; she gained much renown and success despite being a woman and not being traditionally attractive. Thus, critical interpretation of the song renders multiple levels of commentary which represent the coexisting and contradictory cultural spaces that existed in America in the early twentieth century.

Works: Ted Snyder and Irving Berlin: That Opera Rag; Irving Berlin: When the Midnight Choo Choo Leaves for Alabam’ (389).

Sources: Verdi: Miserere from Il Trovatore (387-88); Bizet: Toreador Song from Carmen (389); Donizetti: Sextet from Lucia di Lammermoor (389); Henry Bishop: Home! Sweet Home! from Clari, or the Maid of Milan (389); Ted Snyder and Irving Berlin: That Opera Rag (389-90).

Index Classifications: 1900s, Popular

Contributed by: Nathan Landes