Second-generation Korean experiences in the United States and Canada
Bibliographic record
Abstract
Foreword, Yung Duk Kim Introduction, Pyong Gap Min and Samuel Noh Chapter 1: The Generational Differences in Socioeconomic Attainments of Korean Americans, ChangHwan Kim Chapter 2: Intergenerational Shift in Business Patterns among Korean Americans, Pyong Gap Min and Deborah Kim-Lu Chapter 3: Ethnic Insularity among 1.5- and Second-Generation Korean-American Protestants, Jerry Z. Park Chapter 4: The Intergenerational Differences in Marital Patterns among Korean Americans, Pyong Gap Min and Chigon Kim Chapter 5: Group Membership and Context of Participation in Electoral Politics among Korean, Chinese, and Filipino Americans, Sookhee Oh Chapter 6: Perceived Discrimination and Mental Health in Korean-Canadian Youth: Salience of Ethnic Pride as a Moderator, Il-Ho Kim, Neha Ahmed, and Samuel Noh Chapter 7: Psychological Effects of Discrimination among Korean-Canadian Youth: Role and Salience of Ethnic Identity as a Moderator, Samuel Noh, Il-Ho Kim, and Neha Ahmed Chapter 8: Coping with Racialization: Second-Generation Korean-American Responses to Racial Othering, Dae Young Kim Chapter 9: On Being a Successful Failure: Korean-American Students and the Structural-Cultural Paradox, Nadia Y. Kim and Christine J. Oh Chapter 10: Reassessing the American Dream: Family, Culture and Educational Success among Korean and Chinese Americans, Angie Y. Chung and Trivina Kang Chapter 11: Korean Immigrant High School Students' Identities and Their Impact on School Learning, Minjung Ryu Chapter 12: Are Second-Generation Korean-American Women Tiger Mothers? Strategic, Transnational, and Resistant Responses to Racialized Mothering, Miliann Kang
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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 | 0.000 | 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 | 0.012 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".