Developments in Conceptualizing and Measuring the Emotional Abilities
Bibliographic record
Abstract
Considerable advancement in investigating emotional intelligence (EI) in organizations has been made, including a well-established four factor model of emotional abilities, and through studies that establish that EI matters in the workplace outcomes. However, some valid criticisms remain. Chief among them is the lack of conceptual guidance about treating the emotional abilities as a coherent set of skills to be applied in the service of specific social contexts. Another is the dominance of a single measure of EI, which hinders understanding about the validity of the EI construct. The first two papers in our symposium provide conceptual guidance for thinking about emotional abilities as a coherent set of abilities, with the first paper drawing from established research to argue that a concerted use of emotional skills is required for functional responses. The second paper demonstrates that the combination of two abilities – emotion perception and emotion regulation - are required to foster advantageous social connections. The third and fourth papers introduce new measures. Both aspire to be more than parallel forms of existing measures, introducing innovations in measuring emotional abilities. The third paper introduces a measure that utilizes multimedia presentation of emotional expressions, which increases involvement in emotion perception, lessens demands on test takers, and increases criterion-related validity. The fourth paper introduces a reaction- time based measure of emotion recognition that promises objective scoring and a method to quantify differences in ability. Regulatory Flexibility: A New Perspective on “Intelligent” Coping and Emotion Regulation Presenter: George A Bonanno; Columbia U. Presenter: Charles Levi Burton; Columbia U. The Emotional Stroop Presenter: Hillary Anger Elfenbein; Washington U. in St. Louis Presenter: Daisung Jang; Washington U. in St. Louis Presenter: Sudeep Sharma; Washington U. in St. Louis Presenter: Jeffrey Sanchez-Burks; U. of Michigan New Directions in Assessing Emotion Abilities Presenter: Richard D Roberts; Educational Testing Service Presenter: Carolyn MacCann; The U. of Sydney Presenter: Filip Lievens; Ghent U. Presenter: Jeremy Burrus; Educational Testing Service Presenter: Gerald Matthews; U. of Central Florida Presenter: Ralf Schulze; U. of Wuppertal Relating Emotion Perception and Emotion Regulation Abilities to Network Position Presenter: Shira Agasi; U. of Toronto Presenter: Stephane Cote; U. of Toronto
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".