The Mind Is Its Own Place: Of Lalla’s Comparative Poetics
Bibliographic record
Abstract
What is comparative poetics, and where is it to be found? The tradition of verses in Kashmiri ascribed to the fourteenth-century female ascetic Lalla might seem a strange place to look for answers to these questions, given that the customary parameters of comparative poetics trace disciplinary origins to no earlier than the twentieth century (Earl Miner) and tend to favour a large sample size (the greater the variety of poetic traditions brought under analysis, the likelier the discovery of poetic “universals”). In this article, we offer an account of comparative poetics at work on a much smaller scale and within a distinctive matrix of pressures and principles. Building on the close analysis of Lalla’s verses, we show how her corpus generates multiform “environments” – environments that afford the conceptual and aesthetic alignment of two pre-modern cosmopolitan literary and religious imaginaires, Sanskrit and Persian. In doing so, we call attention to what a comparative poetic endeavour could look like in a pre-modern world by presenting Lalla’s verses as an example of a literary corpus – importantly, not an extra-literary theoretical tradition – that is configured by immanent comparative poetics.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.042 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".