Projecting perfection by hiding effort: supplementing the perfectionistic self-presentation scale with a brief self-presentation measure
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
Extensive research has illustrated the relevance of individual differences in perfectionistic self-presentation, but there has been little work on how perfectionistic self-presentation is expressed. The current research addressed this issue by examining the tendency to project a perfectionistic image by hiding effort. This research develops and evaluates a brief unifactorial measure as an extension of perfectionistic self-presentation. It is shown that the Perfectionistic Self-Presentation Hiding Effort Scale is reliable and valid in terms of its links with multidimensional perfectionism dimensions. Further, individual differences in seeming perfect while hiding effort accounted for unique variance in depression and social anxiety. Factors and processes that contribute to attempting to seem perfect while hiding effort are discussed.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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