Bibliographic record
Abstract
Intergroup marriage has been widely used as an indicator to predict the social integration of immigrants. The assumption is that higher rates of intergroup marriage represent more harmonious outcome of an integrated society. As compared to the U.S., first and 1.5 generation immigrants in Canada have been found to be less likely to intermarry, and their cultural preference of a spouse of the same race/ethnicity has been argued to be the key factor. However, the process of how these immigrants’ cultural preference is maintained in a multicultural context requires exploration. This study elaborates on the role of gossip in the process of the maintaining of ethnic boundaries among recent immigrants using the case of Taiwanese immigrants in Canada. With an examination of their attitudes toward intergroup marriage, the results of the role of gossip indicate, 1) the seemingly impermeable ethnic boundaries established by recent immigrants can be challenged and modified through gossip, and 2) gossip makes the process of integration possible along both horizontal (i.e., coethnic peer of the same cohort) and vertical (i.e., parents to children and vice versa) axis within the same race/ethnic group of immigrants.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.009 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".