Academic Stress and Cultural Coping: The Moderating Effect of Heritage Language Proficiency on Well-Being in a Multilingual Sample
Bibliographic record
Abstract
Coping is a set of behaviours that enable stress management. Traditional theories of coping have examined engagement coping and avoidant coping, but recent work has begun to shed light on culture-specific collective coping strategies. Collective coping varies between cultural groups, but generally helps preserve well-being and reduce psychopathology by affirming an individual’s connection to the rest of their cultural group. Experiments testing this model show that collective coping partially explains the relationship between academic stress and well-being. Language plays a vital role in both the transmission and preservation of cultural information. Given the role of language and communication in regulating the flow of cultural information, one would predict that an individual’s ability to engage in culture-specific coping behaviours would be affected by their linguistic proficiency in their heritage language. In summary, collective coping is theorized to mediate the relationship between academic stress and well-being, and heritage language proficiency is predicted to moderate the effect of collective coping. To test these hypotheses, a multilingual and culturally diverse sample (n = 296) was collected from university campuses in Ontario, Canada. Participants completed a survey that included questionnaires examining academic stress, cultural coping, collective self-esteem, and subjective well-being. The survey also included short-answer questions asking participants to describe collective coping behaviours they use, and their experiences of their heritage language. Structural Equation Modelling was used to test the model for cultural coping. It showed that collective coping mediates the relationship between academic stress and well-being/collective self-esteem (RMSEA = .055 (< .08). Structural Equation Modelling also showed that the addition of a language proficiency moderator variable fit the data (RMSEA = 0.077), and improved overall model quality. Responses to the short answer questions were qualitatively coded. The results showed that participants relied on family, spirituality, and community elders to engage in collective coping. The results also showed that participants who are proficient in their heritage language reported a sense of authenticity and connectedness with their community when afforded the opportunity to speak in their heritage language. Conversely, participants who lacked proficiency in their heritage language reported feeling a sense of embarrassment and dislocation with respect to their heritage language. The results of this project have strong implications for multicultural clinical practice and language revitalization efforts.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".