Multiplicity Across Cultures: Multiple National Identities and Multiple Value Systems
Bibliographic record
Abstract
When we ask ourselves the question ‘Who am I?’, we usually utilize various self-descriptions through which we defined ourselves in the past. Those self-definitions may depend on group memberships, roles and social categories such as culture or religion. We were interested in the question of whether people with dual national identities associate distinct national value systems with each of those identities. In particular, we had focused on first and second generation Asian-Canadians and tested the hypothesis that distinct value systems are linked to each of one’s two national identities. Participants of South-East and East Asian origin or descent completed Schwartz’s (1992) value survey, once as Asians and once as Canadians. The participants revealed discrepancies in how they ranked the value types when instructed to do so as Canadians and as Asians. Specifically, the value types of universalism, self-direction, hedonism and stimulation were rated as significantly more important when participants were responding as Canadians, and the value types of conformity and tradition were rated significantly higher when the same participants were responding as Asians. These results are consistent with the results of other research that compares separate samples in Asia and in the West. But, the present research is fairly unusual in its examination and demonstration of separate value systems within individuals who have two national identities. The implications of having separate value systems associated with each of one’s national identities for the interplay between self-identification and culture and for value theory are discussed.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.015 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".