2024-03-29T01:04:43Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/50022021-11-10T09:38:23Zcom_10259_3830com_10259_5086com_10259_2604col_10259_3832
Briz i Godino, Ivan
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Ahedo García, Virginia
10
500
Álvarez, Myrian
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500
Pal, Nélida .
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500
Turnes, Lucas .
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500
Santos Martín, José Ignacio
526
500
Zurro, Débora
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Caro Saiz, Jorge
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Galán Ordax, José Manuel
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2018-11-09T10:04:08Z
2018-11-09T10:04:08Z
2018-10
2054-5703
http://hdl.handle.net/10259/5002
10.1098/rsos.180906
The present work aims to quantitatively explore and understand the relationship between mobility types (nautical versus pedestrian), specific technological traits and shared technological knowledge in pedestrian hunter–gatherer and nautical hunter–fisher–gatherer societies from the southernmost portion of South America. To that end, advanced statistical learning techniques are used: state-of-the-art classification algorithms and variable importance analyses. Results show a strong relationship between technological knowledge, traits and mobility types. Occupations can be accurately classified into nautical and pedestrian due to the existence of a non-trivial pattern between mobility and a relatively small fraction of variables from some specific technological categories. Cases where the best-fitted classification algorithm fails to generalize are found significantly interesting. These instances can unveil lack of information, not enough entries in the training set, singular features or ambiguity, the latter case being a possible indicator of the interaction between nautical and pedestrian societies.
HAR-2009-06996, CSD2010-00034, HAR2017-
90883-REDC, CULM-HAR2016-77672-P (Ministerio de Ciencia e Innovacio´n de Espan˜ a); PIP-0706, PIP-0348
(Consejo Nacional de Investigaciones Cientı´ficas y Tecnolo´gicas-Argentina) and PICT 2012-2148 (Ministerio de
Ciencia, Tecnologı´a e Innovacio´n Productiva de la Repu´ blica Argentina); PROC/12-120610-A (SESAR WPE Long
Term and Innovative Research-European Commission); and Project GR-7846 (Wenner-Gren Foundation for
Anthropological Research)
application/pdf
eng
The Royal Society
Royal Society Open Science. 2018, V. 5, n. 10, 180906
http://dx.doi.org/10.1098/rsos.180906
info:eu-repo/grantAgreement/MICINN/HAR-2009-06996
info:eu-repo/grantAgreement/MICINN/CSD2010-00034
info:eu-repo/grantAgreement/MICINN/HAR2017-
90883-REDC
info:eu-repo/grantAgreement/MICINN/CULM-HAR2016-77672-P
info:eu-repo/grantAgreement/Consejo Nacional de Investigaciones Científicas y Tecnológicas/PIP-0706
info:eu-repo/grantAgreement/Consejo Nacional de Investigaciones Científicas y Tecnológicas/PIP-0348
info:eu-repo/grantAgreement/Ministerio de
Ciencia, Tecnología e Innovación Productiva/PICT 2012-2148
info:eu-repo/grantAgreement/EC/PROC/12-120610-A
info:eu-repo/grantAgreement/Wenner-Gren Foundation for Anthropological Research/GR-7846
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
hunter–gatherer
statistical learning
shared technology
random forest
mobility
Transporte
Sociología
Transportation
Sociology
Hunter–gatherer mobility and technological landscapes in southernmost South America: a statistical learning approach
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
CC-LICENSE
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oai:riubu.ubu.es:10259/5002
2021-11-10 10:38:23.274
Repositorio Institucional de la Universidad de Burgos
bubrep@ubu.es
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