Review of <i>The People Have Never Stopped Dancing:Native American Modern Dance Histories</i> By Jacqueline Shea Murphy
Bibliographic record
Abstract
In this fascinating, ambitious, and wellresearched book, dance scholar Jacqueline Shea Murphy analyzes three main topics. First she compares the history of U.S. and Canadian government attempts to suppress or transform Indigenous dance between the 1880s and the 1930s and charts the persistence of Native American dance in the face of such pressures. In the second section, she examines how modern dance pioneers such as Ted Shawn and Martha Graham infused modern dance with Indigenous themes. Although Shawn and Graham visited Indian peoples and observed their dance traditions, they ultimately made primitivist use of Indian materials for their own purposes and did not engage meaningfully with Indian worldviews, religions, or political concerns. This section also recovers early Native American choreographers, including Jose Limon and Tom Two Arrows. In the final portion of the book, Murphy explores how Indigenous dance companies use contemporary modern dance as a "tool for spiritual and cultural resilience and self-determination." Murphy's methodology is comprehensive and perhaps unique. She carries out careful archival research but also engages in significant participatory research. In her attempt to avoid the "troublesome dynamics" of the early modern dancers, she attends Indigenous dance workshops, productions, and events and interviews Indigenous dancers and choreographers. Her focus on restrictions on the Sun Dance as well as Plains Indian participation in Buffalo Bill's Wild West Show will particularly interest readers of Great Plains Quarterly.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".