Bibliographic record
Abstract
Introduction: Theorizing Japanese Diaspora Part I: Origins of the Japanese Diaspora Chapter 1: The Japanese Diaspora in the New World: Its Asian Predecessors and Origins Roger Daniels Chapter 2: Japanese Emigration and Immigration: From the Meiji to the Modern James Stanlaw Chapter 3: Instructions to Emigrant Laborers, 1885--1894: in Triumph or Wander on the Verge of Starvation Jonathan Dresner Part II: Cultural Identity: From the Incipient Diaspora to Classic Diaspora Chapter 4: Paradise Lost: Japan's Agricultural Colonists in Manchukuo Greg Guelcher Chapter 5: The Intermarried Issei and Mestizo Nisei in the Philippines: Reflections on Nikkeijin Problems Shun Ohno Chapter 6: Constructing Japanese Brazilian Identity: From Agrarian Migrants to Urban White Collar Workers Chapter 7: A Stone Voice: The Diary of a Japanese Transnational Migrant in Canada Keibo Oiwa Chapter 8: The Japanese of Peru: The First Century Experience and Beyond Daniel Masterson Chapter 9: Japanese Latin Americans during World War II: A Reconsideration Lane Hirabayashi and Akemi Kikumura-Yano Part III: Constructing Identities in the Okinawan, Nikkei, and Permanent Resident Diasporas Chapter 10: Four Governments and a New Land: Emigration to Bolivia Kozy Amemiya Chapter 11: Acting Japanese Gary Okihiro Chapter 12: Crossing Ethnic Boundaries: The Challenge of Brazilian Nikkeijin Return Migrants in Japan Takeyuki Gaku Tsuda Chapter 13: Overseas Japanese and the Challenges of Repatriation in Post-Colonial East Asia Mariko Asano Tamanoi Chapter 14: Negotiating Work and Self: Experiences of Japanese Working Women in Singapore Leng Leng Thang, Miho Goda, and Elizabeth MacLachlan
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.010 | 0.014 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".