More Than a Nation: Toward a New Documentary Poetics
Bibliographic record
Abstract
More Than a Nation: Toward a New Documentary Poetics identifies multiple contexts—Canada, the U.S., Central America, the Southern Cone, and the Caribbean—in which the term “documentary poetry” names a group of twentieth-century literary forms that use a combination of text, images, archival materials, and found discourse to examine historical events. Demonstrating how this type of writing works as a hemispheric nexus of shared aesthetic practices and political concerns even in vastly different cultural contexts, the dissertation considers how poets such as Ernesto Cardenal, Dorothy Livesay, and Aída Cartagena Portalatín translate and rework the language of state and local archives to pose radical critiques of the hegemonic nationalisms which together worked to construct various myths of racial democracy in the postwar period. Speculatively re-imagining narratives of nation-based citizenship to foreground alternative modes of collectivity, these poets shift our categories for thinking the social, offering visions of new worlds ungoverned by colonial violence and white supremacy—even as their individual texts reify, at times, the coloniality of power. The final chapter considers special issues on “Documentary” published by the U.S. literary magazines Chain, edited by Juliana Spahr and Jena Osman, and XCP: Cross Cultural Poetics, edited by Mark Nowak, to chart the late twentieth-century consolidation of “documentary poetry” as an emergent subgenre. The first in-depth study to consider documentary poetry as a phenomenon coeval in English and Spanish language literatures, More Than a Nation goes beyond existing definitional accounts of this emergent genre to understand documentary poetry as an inter-American network of texts employing archival materials, state documents, and print culture—the stuff of “imagined communities”—in the interest of theorizing social belonging beyond the nation-state.
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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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.019 | 0.051 |
| Scholarly communication | 0.030 | 0.022 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 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".