Simply the best? Bridging perfectionism in psychology and girlhood studies
Bibliographic record
Abstract
Perfectionism has been a popular topic of interest in psychological research over the last three decades, with research focusing on youth emerging in the early 2000s. However, the term ‘perfectionism’ is rarely used outside of a psychological framework. Despite lexical differences, girlhood studies researchers have employed a sociocultural lens to study ‘supergirls’: teenage girls who strive to have it all, at all costs. Although these literatures seem to explore a similar phenomenon, they tend to remain disparate. Consequently, this paper argues for the utility of a multidisciplinary framework for studying youth perfectionism to bridge these two seemingly opposite, yet mutually informing, literatures. First, disciplinary understandings of youth who strive for perfection in psychology and girlhood studies, respectively, are summarized. In the following section, a multidisciplinary reading of the extant literature is applied to offer a nuanced account of who a teenage perfectionist may be and how perfectionism might manifest among diverse youth. This article concludes with a call for researchers from both psychological and sociocultural backgrounds to embrace a multidisciplinary framework for research with perfectionistic youth.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.005 |
| 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".