What is the central feature of extraversion? Social attention versus reward sensitivity.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
R. E. Lucas, E. Diener, A. Grob, E. M. Suh, and L. Shao (2000) recently argued that the core of the personality dimension of Extraversion is not sociability but a construct called reward sensitivity. This article accepts their argument that the mere preference for social interaction is not the central element of Extraversion. However, it claims that the real core of the Extraversion factor is the tendency to behave in ways that attract social attention. Data from a sample of 200 respondents were used to test the 2 hypotheses with comparisons of measures of reward sensitivity and social attention in terms of their saturation with the common variance of Extraversion measures. The results clearly showed that social attention, not reward sensitivity, represents the central feature of Extraversion.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 it