Bibliographic record
Abstract
Despite the fact that talent management has risen to a prominent position in managerial discourse, academic research in the field has lagged behind. This article examines talent management, with a specific emphasis on the European environment, and serves as a prelude to the special issue that will be published shortly after. The article and special issue are intended to contribute to the area of talent management by providing a European perspective on work that has been done by colleagues in the United States and Canada. In the aim of providing at the very least a point of departure for the area of talent management in the European environment, we have drawn empirical insights from the European context and coupled them with theoretical methods presented in the different articles. The primary goal of this article is to offer new insights on the link between leadership & talent management. The paper is organized as follows: They tested a concept in which both difficult work circumstances and empowerment moderate the effect of leadership style on organizational commitment, as shown in their research. As a result of the findings, the authors’ conceptual framework appears to be a perfect fit in particular, it has been confirmed that butler leadership has a positive related to trying to challenge work conditions, and that the same workplace conditions are linked to three out of four employee engagement dimensions.
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 | 0.015 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".