Bibliographic record
Abstract
List of Tables and Figures List of Maps Preface Notes on the Contributors Introduction: Community and Identity Among South Asians in Diaspora C.Bates 'They Cannot Represent Themselves': Threats to Difference and So-Called Community Politics in Fiji from 1936-47 J.D.Kelly Nested Identities: Ethnicity, Community and the Nature of Group Conflict in Mauritius A.Nave The Development of Communalism among East African Asians M.Twaddle Imagining? Ethnic Identity and Indians in South Africa R.K.Thiara Migration, Migrant Communities and Otherness in Twentieth Century Sinhala Nationalism in Sri Lanka (up to Independence) N.Wickramasinghe Sojourners and Settlers: South Indians and Communal Identity in Malaysia A.Kaur Communitarian Identities and the Private Sphere: A Gender Dialogue amongst Indo-Trinidadians (1845-1917) S.Chatterjee Hyderabadis in Pakistan: Changing Nations K.Leonard Mohajirs in Pakistan: A Case of Nativisation of Migrants M.Waseem Bridging the Gulf: Migration, Modernity and Identity among Muslims in Mumbai T.B.Hansen Relationships between Muslims and Hindus in the United States: Mlecchas vs Kafirs? A.T.Mohammad Index
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.010 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.003 |
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".