Bibliographic record
Abstract
This paper focuses on the trilogy of feature-length documentaries directed by Ai Weiwei devoted to the global refugee crisis beginning with Human Flow, The Rest and ending with Rohingya. I address the significant thematic and formal differences among these films to consider how these sharpen the aesthetic and political engagement. Against a longstanding photojournalistic repertoire of refugee visualities, I consider how this migration trilogy invites us to think differently about human movement, placelessness, and sense of place, by delicately balancing between images of individuals and (sometimes) talking heads against massive, often abstract aerial/drone backdrops that signpost the shape and scale of migration patterns and displacements. This tension between abstraction and specificity, between scale and detail, enables these films to straddle between varied affective registers and more traditional invocations of melodramatic pathos in ways that foreground the instability and fluidity of documentary’s signifying practices. Rather than adhere strictly to a project of illumination and transparency so foundational to documentary’s ‘jargons of authenticity’, I consider the productive uses of opacity and abstraction across the trilogy, to argue for their political value as strategies that engage the limits of representation while simultaneously bringing visibility to those who exist in globalization’s shadows.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".