How Situational Predictors and Need for Cognitive Closure Shape Coping with Expectation Violations
Bibliographic record
Abstract
Expectations regarding future academic achievement are particularly vulnerable to violations due to their often overly optimistic nature. Therefore, students frequently have to cope with expectation violations. The present study examines how three situational aspects—controllability of expectation (dis-)confirmation, degree of expectation violation, and likelihood of future expectation checks—as well as dispositional Need for Cognitive Closure (NCC) predict coping with expectation violations in the educational context, namely assimilation (i.e., striving for confirmation), accommodation (i.e., expectation change), and immunisation (i.e., ignoring discrepant information). Each situational predictor was expected to be particularly associated with one of the three coping strategies. High controllability was anticipated to facilitate assimilation following unexpected negative feedback, whereas a substantial discrepancy in expectation violation was presumed to encourage accommodation. Additionally, a low likelihood of future expectation checks was predicted to promote immunisation. It was further hypothesised that high NCC would reinforce these tendencies. A vignette experiment was conducted with n = 248 participants. T-tests and MANCOVA confirmed the expected effect of the situational variables on the respective coping strategies. In addition, the association between assimilation and accommodation with these coping strategies was enhanced in individuals with high NCC, suggesting an interaction effect between personality and context in the use of coping strategies. However, NCC did not moderate the association between the risk of future expectation checks and immunisation. Nonetheless, this study provides new insights into the interplay of situational and dispositional predictors of coping with expectation violations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".