Reading of Intertextuality in the Notions of Domestic Violence in Select Texts with Reference to Meena Kandasamy’s When I Hit You
Bibliographic record
Abstract
Intertextuality is a term used to describe how humans read and absorb textual information as a result of the development and interaction of texts. The purpose of this research is to present a theoretical exposition of intertextuality. As a result, the current research focuses on domestic violence, a well-documented social problem that impedes women's development in a variety of ways. The study's methodology is based on the intertextualistic narrative of several works, with a special emphasis on Meena Kandasamy's When I Hit You in the context of Domestic Violence. The study's findings reveal that domestic violence has a vulnerable effect on women due to a range of characteristics, and the analysis of many texts in multiple dimensions suggest that, despite the women characters differing in their cultural medium and familial background, they are intimated by their abusive husbands and are subjected to comparable types of violence worldwide.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".