Extraversion and Counter-Dispositional Behaviour: Exploring Consequences and the Impact of Situation-Behaviour Congruence
Bibliographic record
Abstract
People behave differently from one moment to the next and thus are frequently behaving 'out of character' or counter to their dispositions.Previous research exploring acting out of character indicated that acting extraverted was associated with increases in positive affect for both trait introverts and trait extraverts, whereas acting introverted was associated with cognitive control costs, but only for trait extraverts.These asymmetrical negative consequences can be partially explained by counter-dispositional behaviour as it may consume mental resources through monitoring and modifying behaviour.I proposed that previous research exploring counter-dispositional behaviour has neglected the importance of situational effects.Research demonstrates that contra-normative behaviour is depleting.Previous findings of costs for acting 'out of character' were limited to when behaviour was also incongruent with situational norms.Thus, I extended this line of inquiry by using the acting paradigm in introverted situations.I posited that there would be negative costs associated with acting extraverted, as it was contra-situational.I also posited that there would be even greater costs for dispositional introverts as they were also behaving counter-dispositionally.In two studies, I created introverted situations and randomly assigned participants to one of three experimental conditions (act extraverted, act introverted or control condition).In study 1 (N = 158), participants in the acting extraverted condition reported more positive affect, enjoyment, valence, and authenticity.Furthermore, no effects of cognitive fatigue were found.Thus, the hypothesized costs of acting extraverted were not found.In study 2 (N = 85) acting instructions were modified to highlight the positive features of introversion and the negative features of extraversion.Study 2 also employed naïve confederates so that feedback was uniform across
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".