Bibliographic record
Abstract
GBS_insertPreviewButtonPopup('ISBN:9781853312045); Jazz in American Culture offers an informed and entertaining introduction to jazz - one of the great musical cultures of the world. The book looks at jazz both as a music and as a culture within the wider American context, and aims to open up the subject to the non-specialist. It examines the social and institutional structures that have underpinned the music at particular stages in its history, from the 1930s through to the present, and considers its place as a component of the entertainment industry. Among the musicians introduced are Charlie Parker, Louis Armstrong, Miles Davis, Duke Ellington, Billie Holliday and Lester Young. Peter Townsend's distinctive approach to his subject includes a consideration of representations of jazz in other art forms, including films and literary texts, such as the fiction of Ralph Ellison, Jack Kerouac and Toni Morrison, and the poetry of Langston Hughes. He also introduces the work of jazz-influenced painters such as Stuart Davis and Jackson Pollock, and discusses the significance of photography in jazz. The book also explores the influence of jazz on other art forms, the 'mythology' of jazz, its place in consumer culture and its relation to a number of issues, such as ethnicity and individualism, that have affected American art and society. This book will be of lasting interest to anyone with a passion for jazz music. "
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.015 | 0.005 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".