Subjective well-being of bicultural individuals : understanding person-culture match theory through the lens of acculturation
Bibliographic record
Abstract
In recent years, studies have examined various factors related to person/culture match, a theory that if an individual is similar to the people from a certain cultural environment, it is associated with engagement in positive feelings (Fulmer et al., 2010). There has been extremely limited research in person/culture match and cultural fit regarding bicultural individuals and acculturation. The present research explores how subjective cultural fit, acculturative stress, and social interaction of bicultural individuals are linked to their psychological and subjective well-being using the experience sampling method. In addition, I will be exploring the unique contribution of subjective cultural fit and acculturative stress as independent predictors of well-being, and the reverse causal direction of well-being and subjective cultural fit and acculturative stress. After completing the initial survey, participants were tasked with completing three daily surveys over the span of 10 days. Bicultural participants were asked to fill out questions regarding their moment-to-moment subjective cultural fit and social interaction with Canadians and their own ethnic culture, level of acculturative stress, ratings on their positive and negative affect, life satisfaction, and psychological well-being. Overall, analyses of the results show that subjective cultural fit and social interaction with Canadian culture, and acculturative stress predict bicultural individuals’ well-being, but subjective cultural fit and social interaction with one’s own ethnic culture had no significant effect on well-being. Implications, limitations, and directions for future research are discussed. Keywords: subjective cultural fit, bicultural individuals, acculturation, well-being, culture
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".