How Talent Identification Influences Perceptions of Organizational Justice and Basic Psychological Needs: A Self-Determination Theory Approach
Why this work is in the frame
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Bibliographic record
Abstract
This study aims to explore the impact of talent identification practices on employees' psychological needs and to examine the mediating role of distributive justice/injustice between talent identification and psychological needs. Additionally, it investigates procedural justice/injustice as a moderating variable in this mediation. A cross-sectional sample (n=124) with clinical vignettes was used to test the hypotheses through moderated mediation analysis. The findings reveal three key insights. First, talent identification significantly correlates with psychological needs. High-potential individuals reported greater satisfaction of their needs for autonomy, competence, and relatedness compared to regular employees, who reported higher frustration levels. Second, high potentials perceived greater distributive justice, correlating with increased psychological need satisfaction. Conversely, regular employees perceived higher distributive injustice, leading to greater psychological need frustration. Third, procedural justice/injustice did not significantly moderate the mediation. However, procedural justice/injustice was significantly related to psychological needs, independent of distributive justice/injustice. Our research makes a vital addition to the human resource management (HRM) field by providing quantitative empirical analysis of talent identification where prior work has been largely conceptual or qualitative. Given the current labor market's supply-demand imbalance, understanding these dynamics is increasingly critical.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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