Would introverts be better off if they acted more like extraverts? Exploring emotional and cognitive consequences of counterdispositional behavior.
Bibliographic record
Abstract
People enjoy acting extraverted, and this seems to apply equally across the dispositional introversion-extraversion dimension (Fleeson, Malanos, & Achille, 2002). It follows that dispositional introverts might improve their happiness by acting more extraverted, yet little research has examined potential costs of this strategy. In two studies, we assessed dispositions, randomly assigned participants to act introverted or extraverted, and examined costs-both emotional (concurrent negative affect) and cognitive (Stroop performance). Results replicated and extended past findings suggesting that acting extraverted produces hedonic benefits regardless of disposition. Positive affect increased and negative affect did not, even for participants acting out of character. In contrast, we found evidence that acting counterdispositionally could produce poor Stroop performance, but this effect was limited to dispositional extraverts who were assigned to act introverted. We suggest that the positive affect produced by introverts' extraverted behavior may buffer the potentially depleting effects of counterdispositional behavior, and we consider alternative explanations. We conclude that dispositional introverts may indeed benefit from acting extraverted more often and caution that dispositional extraverts may want to adopt introverted behavior strategically, as it could induce cognitive costs or self-regulatory depletion more generally.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".