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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".