Internal Talent Mobility and Career Development: A Bibliometric Review
Bibliographic record
Abstract
This study presents a bibliometric review of the academic literature on internal talent mobility and career development, aiming to map the intellectual structure, thematic evolution, and collaborative networks within the field. Utilizing data from the Scopus database and analyzed through VOSviewer, the study identifies key trends in author influence, keyword co-occurrence, temporal distribution, and country collaboration. Findings indicate that core topics such as career development, talent management, succession planning, and leadership development form the backbone of the research landscape, while emerging themes like internal consistency, career mobility, and strategic investments signal new directions. The United States leads in scholarly output and international collaboration, with growing contributions from China, Canada, and Germany. Author co-citation analysis reveals strong theoretical foundations, yet the literature remains fragmented across disciplines. The study highlights critical gaps in equity, technology integration, and cross-cultural research, offering a foundation for future exploration. This bibliometric review contributes to the strategic advancement of theory and practice in managing internal talent and fostering sustainable career growth.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".