Entitlement Attitudes Predict Students’ Poor Performance in Challenging Academic Conditions
Bibliographic record
Abstract
Excessive entitlement – an exaggerated or unrealistic belief about what one deserves – has been associated with a variety of maladaptive behaviors, including a decline in motivation and effort. In the context of tertiary education, we reasoned that if students expend less effort to obtain positive outcomes to which they feel entitled, this should have negative implications for academic performance. We tested this hypothesis in a naturalistic experiment in a large course, in which students’ self-reported entitlement attitudes (measured at the beginning of the semester), the idiosyncratic difficulty of the class, and several other individual difference variables associated with academic achievement (personal responsibility, frustration intolerance, and locus of control) were used to predict final exam performance. As expected, greater entitlement was associated with poorer final exam marks, particularly among students for whom the class was objectively challenging. Although no other personality variable qualified the interaction, the extent to which students accepted responsibility for their performance mediated the main effect of entitlement, while external locus of control independently predicted poor exam performance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".