Hiding in Plain Sight: Black Panther, International Law and the “Development Frame”
Bibliographic record
Abstract
This article explores the “troubling antinomies” of the 2018 film Black Panther and its entanglements with the collective fantasies of the West—and those of international lawyers and development technocrats in particular—through its reliance on the “lost world” genre, as typified by H. Rider Haggard’s King Solomon’s Mines and John Buchan’s Prester John. The article then situates these troubling antinomies within the tradition of Black Internationalism and the novels of Pauline Hopkins, George S. Schuyler, and Peter Abrahams as practices of “poetic revolt.” Doing so, it is argued, reveals much about the conditions of possibility of the “development frame” and international law, their shared “White Mythology,” and their ongoing entanglements with history, racial capitalism, and the discourse of technology
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.046 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".