When do personal mindsets predict interest in a culture of growth versus genius? A mindset strength perspective.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Decades of research indicate that growth versus fixed mindsets can influence important outcomes. Some, however, have recently questioned this conclusion, documenting small to nonexistent effects. Inspired by attitudes research, we propose that some growth mindsets may be stronger-more impactful-than others. Specifically, this work examines whether mindsets held with higher certainty are more likely to influence responses. A field study, a high-powered preregistered experiment, and an integrative data analysis test whether mindset certainty influences interest and engagement in organizations that endorse fixed versus growth mindsets. These studies found that when students held their mindsets with high levels of certainty, their personal mindset beliefs were highly predictive of their relative interest in growth versus fixed classrooms, but when they held their mindsets with less certainty, their personal mindsets did not predict relative interest in growth versus fixed classrooms in this same manner. Broadly, these studies support that mindsets vary in strength, which should encourage researchers to identify "when" rather than "whether" growth mindsets predict outcomes. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it