Sympathizing with Social Justice: Poetry of Invitation and Generation
Bibliographic record
Abstract
In this paper, we use Sameshima’s Parallaxic Praxis Model to create collaborative poetry. The model invites juxtaposing articulations to generate alternative thinking. Similar to Daignault's (1992) notion of a “thinking maybe" space, we invite readers into what we call a liminal studio to theorize new understandings of social justice. In the data phases for this project, Viet Thanh Nguyen’s (2015) The Sympathizer served as a play object: The narrator, the sympathizer, is a captured communist spy in the aftermath of the Vietnam war, and his confession (the novel) considers a critical question for understanding social justice: “What is more important than independence and freedom?” Nguyen refuses simplistic overtures of social justice. Instead, readers are confronted with questions: “What do those who struggle against power do when they seize power? What does the revolutionary do when the revolution triumphs? Why do those who call for independence and freedom take away the independence and freedom of others?” (p. 178). These questions lead us to the frame of our own ten-part poem, the modern scholar under interrogation. Our poetry reframes social justice as the art of being/nothing, the something of nothingness being a language of resistance for a reimagined politics.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.026 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".