Bibliographic record
Abstract
This paper conceptualizes Bao Phi’s neologism “refugeography” as a poetics—a mode of expression and a politics, a way of perceiving and being in the world—that critically expands the “refugee” category. Reading Phi’s collection Sông I Sing: Poems (2011), I argue that refugeography signifies the psychic landscape of refugee subjectivity, the scope of refugee subjects (agents and topics), and the physical places of refugee movement and dwelling. This “geographically” capacious concept enlarges the purview of the refugee, insisting that racialization on American shores, police brutality, Asian American identity, diasporic consciousness, and social justice activism along with imperialism, foreign war, and forced migration are “refugee” concerns. For Phi, it is by way of war and empire’s human rem(a)inders that larger issues of identity politics, resistance to oppression, panethnic solidarity, and displacement and rootedness come to the foreground and are shown to be ongoing contemporary contestations in supposedly “post-racial” times. Refugeography thus is an enabling concept, one that begins with the figure of the refugee but does not necessarily end there. It is expansive and wide-ranging in the way it explores and sketches out subjectivities, changing positionalities, and physical geographies while promoting and celebrating Asian American community and identity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".