Unexpected improvement, decline, and stasis: A prediction confidence perspective on achievement success and failure.
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
The authors hypothesized that reactions to performance feedback depend on whether one's lay theory of intelligence is supported or violated. In Study 1, following improvement feedback, all participants generally exhibited positive affect, but entity theorists (who believe that intelligence is fixed) displayed more anxiety and more effort to restore prediction confidence than did incremental theorists (who believe that intelligence is malleable). Similarly, when performance declined, entity theorists displayed more anxiety and compensatory effort than incremental theorists. However, when performance remained rigidly static despite a learning opportunity, incremental theorists evinced more anxiety and compensatory effort than entity theorists. In Study 2, this pattern was replicated when the entity and incremental theories were experimentally manipulated. Study 3 demonstrated that for both groups, theory violation impairs subsequent task performance. Taken together, these studies provide evidence that lay theory violation and damaged prediction confidence have significant and measurable effects on emotion and motivation. The authors discuss the implications of these findings for the literature on achievement success and failure.
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) | 0.000 | 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) | 0.000 | 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 it