Geotropes: Situating Postcolonial Bestsellers in the Global Literary Marketplace
Bibliographic record
Abstract
Conceptions of the literature of the Global South, and of India in particular, have been powerfully shaped by the work of a small number of well-known authors writing in English. The possible distortions resulting from this limited canon have garnered significant scholarly attention in the past two decades, which has typically focused on how works produced by these writers are shaped by their own positionality as well as the exigencies of catering to an Anglo-European metropolitan audience. The concern expressed in such reflections often boils down to that of offering incomplete, skewed, or overly accommodationist representations of the cultures and countries being represented. A corollary of this position is that these same metropolitan readers would be confronted with a different, and potentially quite valuable perspective on the countries and cultures for which these authors have been presumed to speak, were they to encounter a broader swath of the writing produced by local authors writing in indigenous languages. This essay attempts to evaluate and concretize this presumption by way of a computationally assisted analysis. We compare a collection of contemporary English-language novels written by authors of South Asian descent with a corpus of contemporary fiction translated from South Asian languages into English. Using a series of quantitative proxies for two qualities seen as typical of English-language originals — literariness and cosmopolitanism — we aim to establish 1) whether and how the works of the authors writing in English can be seen to constitute a distinctive corpus vis-à-vis the translated works and 2) whether and how the former converge with literary fiction translated from two languages considered to possess high literary capital: French and German. By situating the postcolonial bestsellers within this broader context, we intend to provide a starting point from which to understand the differential pressures exerted by the “otherness industry” on literary production, as well as how reader perceptions of South Asia might be different if they were exposed to a broader range of translated texts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".