Bibliographic record
Abstract
Through a discussion of Mahesh Dattani’s Seven Steps Around the Fire , the first full-length play about hijras that was initially commissioned by the BBC as a radio play in 1999 and was performed in Mississauga in September 2013, this essay highlights the contribution of Indian English drama in attempting to raise global awareness about socially marginalized groups such as the hijra across international sites and contexts. The discussion is informed by debates about the position of English in India, debates that emphasize the need to acknowledge English’s plurality and its various registers and that also suggest the importance of provincializing it in order to scale down the power it commands. However, while most discussions remain focused on the novel and the written text, the prominence accorded to drama in this essay calls attention to the contradictions that continue to mark this genre: while the English language facilitates its global mobility and provides it with an international presence, it simultaneously results in the relegation of this drama to the edges of the overarching category of “Indian” drama because it is written and performed in a language associated with class privilege and colonization in India and is therefore seen as not “Indian.”
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".