Driven, Distracted, or Both? A Performance-Based Ex-Gaussian Analysis of Individual Differences in Anxiety
Bibliographic record
Abstract
Since the inception of the empirical study of personality, and even before it, individual differences in anxiety and distress have been viewed as key predictors of behavioral performance. Yet such literatures have always entertained 2 perspectives, one contending that anxious individuals are "driven" and the other contending that anxious individuals are "distracted." The present 3 studies (total N=289) sought to reconcile such discrepant views according to an ex-Gaussian parsing of reaction time performance tendencies in basic cognitive tasks. As hypothesized, a particular pattern marked by faster responding on the preponderance of trials (in terms of the ex-Gaussian μ parameter) in combination with slower responding on other trials (in terms of the ex-Gaussian τ parameter) was predictive of higher levels of anxiety. Implications for understanding neuroticism, distress, the anxiety-performance interface, and cognitive models of personality processes are discussed.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".