Bibliographic record
Abstract
This volume is the first-ever collection devoted to teaching Beat literature in high school to graduate-level classes. Essays address teaching topics such as the history of the censorship of Beat writing, Beat spirituality, the small press revolution, Beat composition techniques and ELL, Beat multiculturalism/globalism and its legacies, techno-poetics, the road tale, Beat drug use, the Italian-American Beat heritage, Beats and the visual arts of the 1960s, the Beat and Black Mountain confluence, Beat comedy, Beat performance poetry, Beat creative non-fiction, West coast-East/coast Beat communities, and Beat representations of race, gender, class, and ethnicity. Individual essays focus on Gary Snyder’s ecopoetics, William S. Burroughs’s post- and transhumanism, Jack Kerouac’s On the Road (teaching it in the U.S. and abroad) and his Quebecois novels, Allen Ginsberg, Diane di Prima, ruth weiss, Joyce Johnson, Joanne Kyger, Bob Kaufman, and Anne Waldman. Many additional Beat-associated writers, such as Amiri Baraka Gregory Corso, are featured in the other essays. The collection opens with a comprehensive essay by Nancy M. Grace on a history of Beat literature, its reception in and out of academia, and contemporary approaches to teaching Beat literature in multidisciplinary contexts. Many of the essays highlight online resources and other materials proven useful in the classroom. Critical methods range from feminism/gender theory, to critical race theory, formalism, historiography, religious studies, and transnational theory to reception theory. The volume concludes with selected scholarly resources, both primary and secondary, including films, music, and other art forms; and a set of Beat-related classroom assignments recommended by active Beat scholars and teachers.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.438 | 0.312 |
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".