Revealing the Effect of Emotional Intelligence on Organizational Effectiveness: Perspectives from Industrial-Organizational Psychology
Bibliographic record
Abstract
The study reveals the concept of emotional intelligence and its effects on individuals and organizations within the field of Industrial-Organizational psychology. In recent years, emotional intelligence has emerged as a focal point for researchers and practitioners, recognizing its capacity to support various aspects of workplace dynamics, including performance, teamwork, leadership, and overall organizational success. The findings of this research explained the profound impacts of emotional intelligence on a range of employee behaviors and organizational interactions. Individuals with heightened emotional intelligence exhibit advanced communication skills, accurately managing their emotions and articulating themselves effectively. This proficiency extends to conflict resolution scenarios, where individuals demonstrate resilience and approach resolutions with empathy and open-mindedness, fostering enhanced collaboration, stronger interpersonal connections, and heightened group cohesion. The study adopts a triangulation methodology to examine different data sources to ensure the validity and reliability of the research outcomes. Furthermore, the research framework is rooted in Salovey and Mayer's Four-Branch Model of emotional intelligence.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".