Undoing Historical Wrongs: Law and Indigeneity in India
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Beginning with a close look at a recent call by the Supreme Court of India to undo the historical injustices done to the "original inhabitants" of the country, this paper examines similar calls for justice made by Jaipal Singh Munda, the most vocal representative of Adivasis in the Constituent Assembly of India between December 1946 and January 1950, when both the possibilities and limitations of addressing past injustices were being written into the Constitution of India. While drawing attention to debates and disagreements over righting certain past wrongs that remain largely absent from historical accounts of the Constitution's drafting, this paper also invites reflection on the problematique of addressing calls for reparation made by dispossessed peoples as original inhabitants in modern liberal democracies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it