Bibliographic record
Abstract
Abstract This article examines the representation of Prachi, one of the chief subjects of the Indo-Canadian documentary The World Before Her, as a queer girl who finds the space to articulate her non-heteronormativity in a right-wing Hindu training camp for girls, the Durga Vahini. While made in 2012, this Canadian documentary, written and directed by Indo-Canadian film-maker Nisha Pahuja, was released in India in 2014, soon after Narendra Modi’s election, and was criticized by some as being a form of Hindutva propaganda. Drawing on the work of Antke Engel, Nikita Dhawan, Maria do Mar Castro Varela, Akhil Katyal and Kara Keeling, this article looks at the film-maker’s role in shaping the narrative and moments of linguistic, translational and affective excess to argue that queer politics, especially in postcolonial states, is not merely subversive but is also complicit in reinforcing hegemonic ideologies.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.025 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 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".