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
Abstract Language learners’ mindsets–their beliefs about whether language is a fixed aptitude that is immutable or a malleable capacity that can be developed–are associated with achievement goals, language-use anxiety, reappraisals of challenges, and persistence. This study integrates these mindset-related constructs to identify mindset-system profiles among foreign language learners. A latent profile analysis of 234 university students in foreign language courses revealed three distinct profiles. The fixed (21.8%) and growth (20.5%) profiles showed distinct and contrasting patterns of goals, reappraisals, anxiety, and persistence. However, most learners (57.7%) endorsed a mixed profile. Although mindsets alone did not predict grades, students in the growth profile were consistently most engaged and achieved the highest grades, suggesting that mindsets function as a system, in concert with related factors. This person-centered approach enhances our understanding of the complexity and functions of the mindset system, as well as the motivation of learners with mixed mindsets.
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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