Spectacles of Emancipation: Reading Rights Differently in India's Legal Discourse
Bibliographic record
Abstract
How does neo-liberalism change the way we understand rights, law, and justice? With postcolonial and post-liberalization India as its focal point, this article attempts to disrupt the linear, progressive equation that holds that more laws equals more rights equals more justice. This is an equation that has informed and been informed by fundamental rights jurisprudence and law reform, the enactment of legislation to guarantee socio-economic rights, and many of the strategies of social movement activism in contemporary India. This article argues that while these developments have indeed proliferated a public culture of rights, they have simultaneously been accompanied by the militarization of the state and the privatization of state accountability. The result is a cruel paradox in which rights operate as spectacles that make the poor and the disadvantaged continue to repose faith in their emancipatory potential while the managerial and militarized state uses these spectacles to normalize its monopoly over violence. By looking at selected literary, legal, popular, and subaltern texts, the article proposes a radical reimagination of emancipation that is not trapped in the liberal narrative of rights, but rather is embedded in and embodied by the everyday and ordinary struggles of the poor.
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 | 0.010 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.016 | 0.109 |
| Scholarly communication | 0.025 | 0.018 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.010 |
| 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".