Bibliographic record
Abstract
Material Poetics in Hemispheric America examines poets and artists in the Americas during the late twentieth and early twenty-first centuries to show how they worked to make language into material objects and material objects into language. It builds a theory of ‘material poetics’ that provides an alternative account of poetry in hemispheric America. It argues that by reframing American poetry to prominently include object-oriented practices within and beyond the United States, material poetry can be seen as representing a significant branch of the American poetic tradition. This book puts contemporary theories of objects and matter into conversation with a variety of American approaches to material poetics. These approaches result in one-word poems more concerned with the look of language than its meaning, artworks that invite viewers to physically engage with language, poems assembled from networks of out-of-place words and things, poetic monuments that meditate on (and take up) space, and poetry that attempts to materialise the remnants of lyrics and lives. By examining five case studies, drawn from Brazil, Chile, the United States, and Canada, it investigates five ways of conceptualizing these poetic objects—as autonomous, relational, assembled, architectural, and posthuman. Poets and artists featured include Haroldo de Campos, Décio Pignatari, Augusto de Campos, Ferreira Gullar, Hélio Oiticica, Lygia Pape, Juan Luis Martínez, Ronald Johnson, and Anne Carson.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".