Cultural Identity as Part of Youth’s Self-Concept in Multicultural Settings
Bibliographic record
Abstract
Identity is recognized as an important aspect of psychosocial well-being. This study examined the self-concept and cultural identity of 550 youth in a community based sample of high school students in Canada. A revised version of Kuhn and McPartland’s (1954) Twenty Statement Test and Oetting and Beauvais’ (1991) orthogonal cultural identification item were used to gather data. The relationship between participants’ individual (age and gender) and environmental (cultural background and migrant background) with cultural identity levels was considered. Close to 79% of respondents were born in Canada, 18% had immigrated, and 2.5% were visa students. The average age of respondents was 17 years. In relation to self-concept, 61.3% of responses were related to the Self-Evaluations category and 16.5% to the Social Identity category. Five sub-themes (Ethnicity/National origin, Migration status/Residency, Race, Language, and Cultural/Political) were related to cultural identity. Over 54% of the sample identified a lot and 32.5% identified some with the Canadian way of life. Cultural identity levels were found to vary by cultural background in relation to several cultural identity groups. The concept of neighbourhood concordance was considered among the explanations for emerging patterns. The term multiculturation was proposed in cultural identity discourse in multicultural settings.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".