The Relationship Between Career Decision-Making Self-Efficacy and Emotional Intelligence, Career Optimism, Locus of Control and Proactive Personality: A Meta-analysis Study
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
Although there are studies on career decision-making self-efficacy and emotional intelligence, career optimism, locus of control, and proactive personality, no study addresses these four variables together. Therefore, this meta-analysis study examined the correlational findings between career decision-making self-efficacy and four different variables (emotional intelligence, career optimism, locus of control, and proactive personality). In this study, studies published between 1993-2022 examining the relationship between the variables determined from 10 scientific databases (Eric, JSTOR, Sage Journal, Google Academic, Scopus, Springer Ling, Taylor, and Francis ULAKBİM, Proquest, EBSCO) and career decision-making self-efficacy were used. As a result of the research, career decision-making self-efficacy and optimism (r = 0.46; 95% CI [0.33, 0.57]), locus of control (r = 0.36; 95% CI [0.02, 0.62]), proactive personality (r = 0.47; %) 95 CI [0.37, 0.57]) and emotional intelligence (r = 0.45; 95% CI [0.35, 0.54]) were found to be significantly correlated. These critical results point to promising aspects for researchers and practitioners working in career counseling.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 it