Bibliographic record
Abstract
This chapter describes how Amandeep Sidhu converted his concern into action, and more generally, how the efforts of some individual motivated Sikhs coalesced and developed into a Sikh civil rights organization that continues to tackle Sikh civil rights concerns to date. In the wake of 9/11, Sikhs who were arrested for wearing their kirpans, targeted by slurs of &s;Osama bin Laden&s;, &s;raghead&s;, &s;towelhead&s;, &s;diaperhead&s;, and worse, or even firebombed, shot and killed, solely because of their religious appearance. A rare few Sikh Americans may even have had lawyers in their families who inspired them to seek a career steeped in words and laws rather than medicine, or mathematics, or engineering or business all more common vocations than the law for Sikh immigrants. Communities in which Sikhs have segregated themselves, and refused to participate in daily civic activities, tend to be those communities in which nameless, faceless cowards have felt free to attack families.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.590 | 0.257 |
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".