An Examination of the Diverse Interpretations of the Epic through the Paradigm of Queer Theory and the Contradiction of the Self and Society
Bibliographic record
Abstract
The article is of the conceptual epilogue, which provides a concise elucidation by delineating distinct sets of correlations. It examines the gender dichotomy, obscured self, and Marginalization of the selected characters in the reinterpreted works of Mahabharata. "Queer is an umbrella term for those individuals who are not only deemed sexually deviant but are made to feel marginalised due to standard social practices. It is a site of permanent becoming" (Giffney, 2004, p. 67). This study draws upon the post-modernist technique of reinterpretation to examine and reflect upon stereotypes, authority, and sexist values in Queer perspective. It also aims to challenge and mitigate gender distinctions, emotional perception, and the facilitation of women's thoughts and understanding. By giving voice to marginalised characters, the authors explore their ongoing struggle with the complexities of sex and gender, the rigidity between personal desires and societal obligations, and the intricate interplay between individual and collective truths. In doing so, they present a myriad of potential subjectivities and imaginative possibilities that shed light on contemporary issues surrounding Identity and self-perception.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.040 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| 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".