Living at the Crossroads of Cultural Worlds: The Experience of Normative Conflicts by Second Generation Immigrant Youth
Bibliographic record
Abstract
Abstract The children of immigrants are often referred to as second‐generation youth. Although there is tremendous diversity among them, they often share the common experience of being bicultural by holding both heritage and mainstream cultural identities. Given that cultures generally promote similar expectations for youth (e.g., showing respect for parents), holding two cultural identities is not necessarily problematic. Even when cultural expectations do differ, these individuals can typically switch between cultural identities (e.g., South Asian at home; mainstream Canadian at school) as a strategy to avoid conflict. For some issues, however, switching between identities will not resolve the conflict because fulfilling the normative expectations associated with one identity is done at the expense of the ones of the other identity (e.g., choosing a romantic partner that is either from the heritage culture or from mainstream culture). The current paper presents a normative approach to understanding the experience of culturally‐based conflicts among second‐generation youth. In addition, research stemming from this normative approach in the area of intimate relationships is presented to further illustrate the value of the model in understanding the potential cultural conflicts of second‐generation youth and how they may be negotiated.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".