# Career on the Move: Geography, Stratification, and Scientific Impact

arXiv: https://arxiv.org/abs/1404.6247 · HTML: https://mlsanity.com/paper/1404.6247/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 Apr 2014.

## Built on by (most cited first, 4 of 4)

- [China and the U.S. produce more impactful AI research when collaborating together](https://mlsanity.com/paper/2304.11123/) (2023)
- [Paths of A Million People: Extracting Life Trajectories from Wikipedia](https://mlsanity.com/paper/2406.00032/) (2024)
- [Predicting Star Scientists in the Field of Artificial Intelligence: A Machine Learning Approach](https://mlsanity.com/paper/2407.14559/) (2024)
- [Decoding Digital Influence: The Role of Social Media Behavior in Scientific Stratification Through Logistic Attribution Method](https://mlsanity.com/paper/2407.15854/) (2024)

## Abstract (arXiv)

Changing institutions is an integral part of an academic life. Yet little is known about the mobility patterns of scientists at an institutional level and how these career choices affect scientific outcomes. Here, we examine over 420,000 papers, to track the affiliation information of individual scientists, allowing us to reconstruct their career trajectories over decades. We find that career movements are not only temporally and spatially localized, but also characterized by a high degree of stratification in institutional ranking. When cross-group movement occurs, we find that while going from elite to lower-rank institutions on average associates with modest decrease in scientific performance, transitioning into elite institutions does not result in subsequent performance gain. These results offer empirical evidence on institutional level career choices and movements and have potential implications for science policy.