Bibliographic record
Abstract
n celebrating the epistemological reform and empowerment of non-white peoples in the academy, we propose a manifesto that seeks to dislodge the complacencies within Sikh Studies and within Sikh communities, and invite non-Sikhs to engage with radical Sikhi social justice. By dwelling at feminist intersections of postcolonial studies, decolonial studies, and decolonization studies, we are inspired to share the radical possibilities of Sikh Studies, and we also urge Sikh Studies and Sikh people to inhabit an explicit political orientation of insurrection and subversion. Importantly, such a feminist decolonial orientation may well hold promise for other fields of study on the margins as well. In particular, we foreground eight points of action: gendering Sikh Studies; de-policing intimate desire and the diversity of relationships; disrupting Eurocentric knowledge production; de-territorializing diasporas; challenging caste politics; disrupting Islamophobia; undoing our roles in contemporary colonialisms; and fostering care and responsibility for the nonhuman world. In this manifesto we hope to develop interdisciplinary connections, critical interventions, and broader alliances to cultivate debates and action that both challenge tradition and participatewithin broader political campaigns for social justice.
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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 | 0.011 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.035 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".