Bibliographic record
Abstract
This ambitious work confronts the complex question of who and what is a Nikkei, that is, a person of Japanese descent, by studying their communities in seven countries in the Americas: Argentina, Bolivia, Brazil, Canada, Paraguay, Peru, and the United States. It also considers the special case of the many Latin American Nikkei who have returned to Japan in recent decades to seek employment. The contributors draw upon a range of disciplines to present a multifaceted portrait of people of Japanese descent in the Americas, the destination of 90 percent of Japanese emigrants. Thus, for example, the reader is able to view the Peruvian Japanese experience through the eyes of an anthropologist, a demographer/historian, and a journalist—all of whom are Peruvians of Japanese descent. Among the main questions explored in New Worlds, New Lives are: What is the historical background and current status of Nikkei society in a given country? Are there any common attributes the Nikkei share across the Americas, especially in terms of social institutions, the family, the position of women, religion, education, politics, and economics? What are the significant differences between the Nikkei populations in the various countries and why have these differences developed? What are the future prospects of Nikkei communities in the Americas?
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.009 | 0.015 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".