(Un)Sympathetic Species: Kin and Kind in Teju Cole’s <i>Open City</i>
Bibliographic record
Abstract
Abstract Teju Cole’s Open City is one of several recent postcolonial novels that narrate the refugee crisis and the threats to nonhuman species in a way that takes seriously the parallels and interspecies relationships. I am interested in the extent to which novels that explore kinships across boundaries of kind manage to make a space for the nonhuman in the anthropocentric form of the novel. In the case of Open City , I argue that Cole’s figural approach offers a means of formalizing the human representation of nonhuman others as a problem and allows readers to make connections across species boundaries even as the novel raises the specter of moral stasis through the cosmopolitan narrator’s failure to take an ethical stance with respect to those in search of refuge, human or not. This failure is a human one, and in offering an anatomy of such a failure, Cole invites scrutiny of cosmopolitanism as much as of the novel form’s anthropocentrism.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".