A Tale of Two Global Cities: The State of Asian Americans in Los Angeles and New York
Bibliographic record
Abstract
At the national level, the Asian American population has grown more than any other major race group.According to the 2010 Census, the Los Angeles metro area had 2,199,186 Asians, making it the home to the largest Asian population in the United States.Following close behind was the New York City metro area with 2,008,906 Asians.Over a quarter of the 14.7 million Asian Americans reside in either of the two greater metropolitan regions, where they comprise around a tenth of the total population in each metropolis.We begin with a brief historical overview of immigration legislation that has both invited and excluded Asian Americans, as a means of understanding how Asian Americans have been perceived over time.We will also compare some key characteristics of Asian American populations in Los Angeles County, New York City, the Balance of LA Combined Statistical Area (CSA) (excluding Los Angeles County), and the Balance of NYC CSA (excluding New York City), and the Balance of United States.The paper will cover: (1) demographic trends and patterns (2) economic status (3) political engagement and incorporation, and (4) residential settlement patterns.We close with a discussion of how these demographic changes have contributed to Asian Americans rapid social, economic, and political upward mobility in the last decade, at a time when the global restructuring of the economy has blurred nation-state boundaries that once existed and migration from Asia to the United States has become more complex, particularly over the past two decades.
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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 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".