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Author Credit for Transdisciplinary Collaboration

Transdisciplinary collaboration is the key for innovation. An evaluation mechanism is necessary to ensure that academic credit for this costly process can be allocated fairly among coauthors. This paper proposes a set of quantitative measures (e.g., t_credit and t_index) to reflect authors’ transdis...

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Detalles Bibliográficos
Autores principales: Xu, Jian, Ding, Ying, Malic, Vincent
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4574108/
https://www.ncbi.nlm.nih.gov/pubmed/26375678
http://dx.doi.org/10.1371/journal.pone.0137968
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author Xu, Jian
Ding, Ying
Malic, Vincent
author_facet Xu, Jian
Ding, Ying
Malic, Vincent
author_sort Xu, Jian
collection PubMed
description Transdisciplinary collaboration is the key for innovation. An evaluation mechanism is necessary to ensure that academic credit for this costly process can be allocated fairly among coauthors. This paper proposes a set of quantitative measures (e.g., t_credit and t_index) to reflect authors’ transdisciplinary contributions to publications. These measures are based on paper-topic probability distributions and author-topic probability distributions. We conduct an empirical analysis of the information retrieval domain which demonstrates that these measures effectively improve the results of harmonic_credit and h_index measures by taking into account the transdisciplinary contributions of authors. The definitions of t_credit and t_index provide a fair and effective way for research organizations to assign credit to authors of transdisciplinary publications.
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spelling pubmed-45741082015-09-18 Author Credit for Transdisciplinary Collaboration Xu, Jian Ding, Ying Malic, Vincent PLoS One Research Article Transdisciplinary collaboration is the key for innovation. An evaluation mechanism is necessary to ensure that academic credit for this costly process can be allocated fairly among coauthors. This paper proposes a set of quantitative measures (e.g., t_credit and t_index) to reflect authors’ transdisciplinary contributions to publications. These measures are based on paper-topic probability distributions and author-topic probability distributions. We conduct an empirical analysis of the information retrieval domain which demonstrates that these measures effectively improve the results of harmonic_credit and h_index measures by taking into account the transdisciplinary contributions of authors. The definitions of t_credit and t_index provide a fair and effective way for research organizations to assign credit to authors of transdisciplinary publications. Public Library of Science 2015-09-16 /pmc/articles/PMC4574108/ /pubmed/26375678 http://dx.doi.org/10.1371/journal.pone.0137968 Text en © 2015 Xu et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Xu, Jian
Ding, Ying
Malic, Vincent
Author Credit for Transdisciplinary Collaboration
title Author Credit for Transdisciplinary Collaboration
title_full Author Credit for Transdisciplinary Collaboration
title_fullStr Author Credit for Transdisciplinary Collaboration
title_full_unstemmed Author Credit for Transdisciplinary Collaboration
title_short Author Credit for Transdisciplinary Collaboration
title_sort author credit for transdisciplinary collaboration
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4574108/
https://www.ncbi.nlm.nih.gov/pubmed/26375678
http://dx.doi.org/10.1371/journal.pone.0137968
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