The mindsets × societal norm effect across 78 cultures: Growth mindsets are linked to performance weakly and well‐being negatively in societies with fixed‐mindset norms
Bibliographic record
Abstract
BACKGROUND/AIMS: Recent research on mindsets has shifted from understanding its homogenous role on performance to understanding how classroom environments explain its heterogeneous effects (i.e., Mindsets × Context hypothesis). Does the macro context (e.g., societal level of student mindsets) also help explain its heterogeneous effects? And does this interaction effect also apply to understanding students' well-being? To address these questions, we examined whether and how the role of students' mindsets in performance (math, science, reading) and well-being (meaning in life, positive affect, life satisfaction) depends on the societal-mindset norms (i.e., Mindsets × Societal Norm effect). SAMPLE/METHODS: We analysed a global data set (n = 612,004 adolescents in 78 societies) using multilevel analysis. The societal norm of student mindsets was the average score derived from students within each society. RESULTS: Growth mindsets positively and weakly predicted all performance outcomes (rs = .192, .210, .224), but the associations were significantly stronger in societies with growth-mindset norms. In contrast, the associations between growth mindsets and psychological well-being were very weak and inconsistent (rs = -.066, .003, .008). Importantly, the association was negative in societies with fixed-mindset norms but positive in societies with growth-mindset norms. CONCLUSIONS: These findings challenge the idea that growth mindsets have ubiquitous positive effects in all societies. Growth mindsets might be ineffective or even detrimental in societies with fixed-mindset norms because such societal norms could suppress the potential of students with growth mindsets and undermines their well-being. Researchers should take societal norms into consideration in their efforts to understand and foster students' growth.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 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".