The Contributions of Personality Traits and Emotional Intelligence to Intrapreneurial Self-Capital: Key Resources for Sustainability and Sustainable Development
Bibliographic record
Abstract
In the innovative research area of the psychology of sustainability and sustainable development, Intrapreneurial Self-Capital (ISC) constitutes a promising core of resources to face the challenges of the 21st century. This article presents two studies supporting the contribution of trait emotional intelligence to ISC beyond that explained by the three most quoted personality trait models. The Intrapreneurial Self-Capital Scale (ISCS), Trait Emotional Intelligence Questionnaire Short Form (TEIQue-SF), Big Five Questionnaire (BFQ), Mini International Personality Item Pool Scale (Mini-IPIP), HEXACO-60, and Eysenck Personality Questionnaire Revised Short Form (EPQ-RS) were administered to 210 first and second year university students (Study 1) and 206 university students in the last three years of undergraduate university studies (Study 2). Hierarchical regression analyses demonstrated that Emotional Intelligence (EI) explained additional variance in ISC beyond that accounted for each of the three personality trait models for both samples. These results should encourage future research within a positive primary prevention perspective in the framework of the psychology of sustainability and sustainable development.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".