Negotiating Music and Politics: John Cageâs United States Bicentennial Compositions âLecture on the Weatherâ and âRenga with Apartment House 1776â
Bibliographic record
Abstract
abstract: In 1975 the Canadian Broadcasting Company (CBC) invited John Cage to write a composition for the bicentennial birthday of the United States. The result was Lecture on the Weather, a multi-media work for twelve expatriate vocalists and/or players with independent sound systems, magnetic tape, and film. Cage used texts by Henry David Thoreau, recordings of environmental sounds made by American composer Maryanne Amacher and a nature-inspired film by Chilean visual artist Luis Frangella. The composition opens with a spoken Preface and is arguably one of Cage’s most overtly political pieces. A year later the National Endowment of the Arts (NEA) and six major United States orchestras commissioned Cage to compose another work commemorating the United States bicentennial of the American Revolution. In response, he created Renga with Apartment House 1776, which follows his concept of a “music circus,” or simply, a musical composition with a multiplicity of events occurring simultaneously. Scored for voices, instrumental soloists and quartets, Renga with Apartment House is a multi-faceted work marked by layers of American hymns and folk tunes. \n\n \tCage’s United States Bicentennial compositions – and his other pieces created in the 1970s and 1980s – have received little attention from music scholars. Unique and provocative works within his oeuvre, these compositions raise many questions. Why was Cage commissioned to write these works? How did Cage pay tribute to this celebratory event in American history? What socio–political meanings are implied in these pieces? In this thesis I will provide political, cultural, and biographical contexts of these works. I will further examine their genesis, analyze their scores and selected performances, reflect on their meaning and critical implications and consider the reception of these works. My research draws on unpublished documents housed in the CBC’s archives at McGill University, the archives of C. F. Peters, the New York Public Library and it builds on research of such scholars as David W. Bernstein, William Brooks, Benjamin Piekut, and Christopher Shultis. This thesis offers new information and perspectives on Cage’s creative work in the 1970s and aims at filling a significant gap in Cage scholarship.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.021 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".