Perfectionism and Life Narratives: A Qualitative Study
Bibliographic record
Abstract
We examined how perfectionistic people conceptualize perfectionism and narrate life events using thematic analysis. Participants included 20 university students who qualified as highly perfectionistic based on cutoffs on the Almost Perfect Scale–Revised ( n = 6 adaptive, n = 14 maladaptive). Participants completed a qualitative interview. Using thematic analysis, we identified five themes regarding participants’ conceptualization of perfectionism. The most common themes supported prior theory (high personal standards, performance is never good enough), along with a few comparatively understudied themes (being neat and orderly, feels superior to others, gets caught up in the details). We also identified five themes in a life narrative interview (relationship success, relationship problems, agentic redemption, agentic contamination, and academic success), which provided insight into how young, perfectionistic university students create meaning and identity through autobiographical narratives. “Relationship success” themes were most central to adaptive perfectionists, whereas “agentic redemption” themes were most central to maladaptive perfectionists.
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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 | 0.014 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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 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".