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Mapping Manuel Sandoval Vallarta (1899–1977) Scientific Contribution
This paper employs network theory, mining data and bibliometric analysis when mapping the scientific contribution of Nobel Prize candidate; Manuel Sandoval Vallarta, the first and most renowned Mexican physicist and important figure in Latin American science. Vallarta died in 1977, and the existing...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516536/ https://www.ncbi.nlm.nih.gov/pubmed/36187324 http://dx.doi.org/10.1007/s10699-022-09872-y |
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author | Ramos-Lara, María de la Paz Carreón-Vázquez, Gustavo Acatitla-Romero, Edgar Mendoza-Rosas, Rosa María |
author_facet | Ramos-Lara, María de la Paz Carreón-Vázquez, Gustavo Acatitla-Romero, Edgar Mendoza-Rosas, Rosa María |
author_sort | Ramos-Lara, María de la Paz |
collection | PubMed |
description | This paper employs network theory, mining data and bibliometric analysis when mapping the scientific contribution of Nobel Prize candidate; Manuel Sandoval Vallarta, the first and most renowned Mexican physicist and important figure in Latin American science. Vallarta died in 1977, and the existing literature is about his life and contributions to science but not about how those are still valuable today. This paper is the first to highlight, with mapping tools, that his contributions are relevant to the international community of cosmic rays (as he was pioneer and leader), quantum mechanics and relativity. These tools delivered three findings: Identify how he built his own field of study, same as universal knowledge. Unveil that the backward and forward Vallarta citations follow a scale-free network distribution. Determine social factors that benefited or affected his scientific activities—such as World War II interrupting Vallarta’s successful productivity at Massachusetts Institute of Technology. Furthermore, this study confirmed the interdisciplinary nature of the mapping studies of the scientist's contributions using scientometric tools. As a result, several interesting questions arose throughout our research, some of which were answered from the history and philosophy of science. However, others need to be analyzed by experts in the fields of Vallarta. Mapping research sends an invitation to interdisciplinary dialogue/research between experts in different areas of study to better understand the process of knowledge production both, individual and collective. |
format | Online Article Text |
id | pubmed-9516536 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-95165362022-09-28 Mapping Manuel Sandoval Vallarta (1899–1977) Scientific Contribution Ramos-Lara, María de la Paz Carreón-Vázquez, Gustavo Acatitla-Romero, Edgar Mendoza-Rosas, Rosa María Found Sci Article This paper employs network theory, mining data and bibliometric analysis when mapping the scientific contribution of Nobel Prize candidate; Manuel Sandoval Vallarta, the first and most renowned Mexican physicist and important figure in Latin American science. Vallarta died in 1977, and the existing literature is about his life and contributions to science but not about how those are still valuable today. This paper is the first to highlight, with mapping tools, that his contributions are relevant to the international community of cosmic rays (as he was pioneer and leader), quantum mechanics and relativity. These tools delivered three findings: Identify how he built his own field of study, same as universal knowledge. Unveil that the backward and forward Vallarta citations follow a scale-free network distribution. Determine social factors that benefited or affected his scientific activities—such as World War II interrupting Vallarta’s successful productivity at Massachusetts Institute of Technology. Furthermore, this study confirmed the interdisciplinary nature of the mapping studies of the scientist's contributions using scientometric tools. As a result, several interesting questions arose throughout our research, some of which were answered from the history and philosophy of science. However, others need to be analyzed by experts in the fields of Vallarta. Mapping research sends an invitation to interdisciplinary dialogue/research between experts in different areas of study to better understand the process of knowledge production both, individual and collective. Springer Netherlands 2022-09-28 /pmc/articles/PMC9516536/ /pubmed/36187324 http://dx.doi.org/10.1007/s10699-022-09872-y Text en © The Author(s), under exclusive licence to Springer Nature B.V. 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Article Ramos-Lara, María de la Paz Carreón-Vázquez, Gustavo Acatitla-Romero, Edgar Mendoza-Rosas, Rosa María Mapping Manuel Sandoval Vallarta (1899–1977) Scientific Contribution |
title | Mapping Manuel Sandoval Vallarta (1899–1977) Scientific Contribution |
title_full | Mapping Manuel Sandoval Vallarta (1899–1977) Scientific Contribution |
title_fullStr | Mapping Manuel Sandoval Vallarta (1899–1977) Scientific Contribution |
title_full_unstemmed | Mapping Manuel Sandoval Vallarta (1899–1977) Scientific Contribution |
title_short | Mapping Manuel Sandoval Vallarta (1899–1977) Scientific Contribution |
title_sort | mapping manuel sandoval vallarta (1899–1977) scientific contribution |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516536/ https://www.ncbi.nlm.nih.gov/pubmed/36187324 http://dx.doi.org/10.1007/s10699-022-09872-y |
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