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Quantifying hierarchy and prestige in US ballet academies as social predictors of career success

In the recent decade, we have seen major progress in quantifying the behaviors and the impact of scientists, resulting in a quantitative toolset capable of monitoring and predicting the career patterns of the profession. It is unclear, however, if this toolset applies to other creative domains beyon...

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Autores principales: Herrera-Guzmán, Yessica, Gates, Alexander J., Candia, Cristian, Barabási, Albert-László
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616162/
https://www.ncbi.nlm.nih.gov/pubmed/37903804
http://dx.doi.org/10.1038/s41598-023-44563-z
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author Herrera-Guzmán, Yessica
Gates, Alexander J.
Candia, Cristian
Barabási, Albert-László
author_facet Herrera-Guzmán, Yessica
Gates, Alexander J.
Candia, Cristian
Barabási, Albert-László
author_sort Herrera-Guzmán, Yessica
collection PubMed
description In the recent decade, we have seen major progress in quantifying the behaviors and the impact of scientists, resulting in a quantitative toolset capable of monitoring and predicting the career patterns of the profession. It is unclear, however, if this toolset applies to other creative domains beyond the sciences. In particular, while performance in the arts has long been difficult to quantify objectively, research suggests that professional networks and prestige of affiliations play a similar role to those observed in science, hence they can reveal patterns underlying successful careers. To test this hypothesis, here we focus on ballet, as it allows us to investigate in a quantitative fashion the interplay of individual performance, institutional prestige, and network effects. We analyze data on competition outcomes from 6363 ballet students affiliated with 1603 schools in the United States, who participated in the Youth America Grand Prix (YAGP) between 2000 and 2021. Through multiple logit models and matching experiments, we provide evidence that schools’ strategic network position bridging between communities captures social prestige and predicts the placement of students into jobs in ballet companies. This work reveals the importance of institutional prestige on career success in ballet and showcases the potential of network science approaches to provide quantitative viewpoints for the professional development of careers beyond science.
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spelling pubmed-106161622023-11-01 Quantifying hierarchy and prestige in US ballet academies as social predictors of career success Herrera-Guzmán, Yessica Gates, Alexander J. Candia, Cristian Barabási, Albert-László Sci Rep Article In the recent decade, we have seen major progress in quantifying the behaviors and the impact of scientists, resulting in a quantitative toolset capable of monitoring and predicting the career patterns of the profession. It is unclear, however, if this toolset applies to other creative domains beyond the sciences. In particular, while performance in the arts has long been difficult to quantify objectively, research suggests that professional networks and prestige of affiliations play a similar role to those observed in science, hence they can reveal patterns underlying successful careers. To test this hypothesis, here we focus on ballet, as it allows us to investigate in a quantitative fashion the interplay of individual performance, institutional prestige, and network effects. We analyze data on competition outcomes from 6363 ballet students affiliated with 1603 schools in the United States, who participated in the Youth America Grand Prix (YAGP) between 2000 and 2021. Through multiple logit models and matching experiments, we provide evidence that schools’ strategic network position bridging between communities captures social prestige and predicts the placement of students into jobs in ballet companies. This work reveals the importance of institutional prestige on career success in ballet and showcases the potential of network science approaches to provide quantitative viewpoints for the professional development of careers beyond science. Nature Publishing Group UK 2023-10-30 /pmc/articles/PMC10616162/ /pubmed/37903804 http://dx.doi.org/10.1038/s41598-023-44563-z Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Herrera-Guzmán, Yessica
Gates, Alexander J.
Candia, Cristian
Barabási, Albert-László
Quantifying hierarchy and prestige in US ballet academies as social predictors of career success
title Quantifying hierarchy and prestige in US ballet academies as social predictors of career success
title_full Quantifying hierarchy and prestige in US ballet academies as social predictors of career success
title_fullStr Quantifying hierarchy and prestige in US ballet academies as social predictors of career success
title_full_unstemmed Quantifying hierarchy and prestige in US ballet academies as social predictors of career success
title_short Quantifying hierarchy and prestige in US ballet academies as social predictors of career success
title_sort quantifying hierarchy and prestige in us ballet academies as social predictors of career success
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10616162/
https://www.ncbi.nlm.nih.gov/pubmed/37903804
http://dx.doi.org/10.1038/s41598-023-44563-z
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