Women and the Sikh Diaspora in California : Singing the Seven Seas
Bibliographic record
Abstract
This book charts the transoceanic history of South Asian women in California through their speech and songs across the twentieth century. Nicole Ranganath reimagines the history of the South Asian diaspora through an examination of gender and the dynamic interplay of water and land in the cultural history of Sikhs, a faith and cultural community that emerged in the Punjab region of north South Asia over 550 years ago. It shows how the history and music of transoceanic communities, in this case Sikhs, spilled beyond the boundaries of regions, empires and nation-states. It emphasizes the heterogeneity of the South Asia diaspora by uncovering the distinct history of women’s migration experiences, as well as an alternative oceanic imaginary among Sikhs that envisions unity in the cosmos. It foregrounds the pivotal role that women played in transforming Sikh communities in California through songs and female affinities. Based on six years of fieldwork in rural northern California, it explores song as a window into the interior lives of Sikh women through their performance of diverse genres: gadar anti-colonial songs, folk music, hymns, and autobiographical songs. This sonic history of South Asian women in the diaspora dislodges dominant paradigms in diaspora studies and oceanic humanities that depict men as mobile and women as stationary. Women and the Sikh Diaspora in California will interest scholars of migration, South Asia and South Asian American studies, oceanic humanities, Sikh studies, music, and women’s studies. It is also essential reading for anyone who is curious about global music and migration, as well as Sikh history.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.005 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".