Communal Violence, Trauma and Dislocation: Females of Badami’s Can You Hear the Nightbird Call?
Bibliographic record
Abstract
Women have always been a victim of one or another type of violence whether it is communal, political, social, or domestic. Anita Rau Badami’s Can You Hear the Nightbird Call? in its backdrop has communal violence which happened in India and across borders where women figure is at the receiving end. The three female characters Bibiji, Leela and Nimmo face victimization and trauma due to the Sikh separatist movement which has its echoes in Canada also, and the 1984 Anti-Sikh riots in India as Bibiji and Nimmo suffer the loss of men in their lives and Leela has to lose her life in air tragedy. The violence travels across distance and space and affects these women irrespective of their location, community, or social status. The present paper offers to critically analyze Badami’s work and explores how communalism is essentially a politicized event that eventually victimizes the innocent and helpless commoners specifically the women who bear the brunt of it.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".