Striving to reach the “native speaker standard”: A growth belief may mitigate some deleterious effects of social comparison in migrants
Bibliographic record
Abstract
While upward social comparison can inspire and provide information for self-improvement, it can also threaten one’s self-confidence. This study examines how upward comparisons with “native speakers” relate to self-confidence and adaptation of migrant students who speak English as a second language, and the role of language mindsets in this process. Study 1 ( n = 322) showed that the majority of migrant university students (67 %) tend to compare themselves with native speakers or people with higher levels of English proficiency (i.e., upward comparison), but those with fixed (vs. growth) mindsets were less likely to do so. Study 2 ( n = 101) showed that when migrant students compared to native speakers (vs. control), they reported lower level of confidence. However, some negative effects of social comparison were buffered by growth mindsets, such that people with growth (vs. fixed) mindsets were less anxious and more confident to adapt to their academic environment. These findings suggest the “native speaker standard” has detrimental effects on linguistic-minority students’ language, social, and academic adaptations, but a growth mindset might mitigate some of these negative effects. • Most migrant students in North America compare themselves to “native English speakers.” • The “native speaker standard” undermines migrants’ emotion and adaptation. • Growth mindsets buffer some negative effects, specifically on language anxiety and academic adaptation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".