Bibliographic record
Abstract
Abstract The early twentieth century ushered in an exciting wave of avant-garde artistic innovation. While Igor Stravinsky was thinking about new ways of interpreting sound, Pablo Picasso was exploring new ways of representing the figure, and Coco Chanel was giving women a new sense of style. Within this moment of avant-garde change, few recognized black women artistes and intellectuals who were also driving cultural innovation and were agents of molding and shaping Western culture and society. This book uncovers the forgotten story of one such woman called Elsie Houston—a mixed-race, Brazilian, classically trained soprano. Following her artistic and social networks from Brazil to Paris and then on to New York, this book opens the door to an unexpected history of race, sexuality, and society during the twentieth century. Elsie captured the 1920s and 1930s Western artistic vogue for black exotica by restylizing Afro-Brazilian folk songs on elite stages. In Paris, she became the ultimate flapper girl: she performed in one of the city’s risqué nudist cabarets; moved in the same social circles as the likes of Josephine Baker; became a muse for Man Ray; and engaged the same political sphere as the Trotskyists. After her move to New York City in 1937, the press branded her folk songs as “voodoo” and she was part of a bohemian set of figures who were connected to the Harlem Renaissance such as Carl Van Vechten and Virgil Thomson. Elsie reconceptualized black music, in particular Afro-Brazilian music, as modern and cosmopolitan.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.271 | 0.074 |
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".