Datasets from papers under evaluation or published in Humanities & Social Sciences Communications (as well as Palgrave Communications until June 2020), which is an open-access online-only journal dedicated to publishing high quality original research across all areas of the humanities, and the social and behavioural sciences.
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71 to 80 of 106 Results
Nov 19, 2020
Dong, Sicong; Huang, Chu-Ren; Yang, Yike; Ren, He, 2020, "Replication Data for: From language to meteorology: kinesis in weather events and weather verbs across Sinitic languages", https://doi.org/10.7910/DVN/REQ51X, Harvard Dataverse, V1, UNF:6:B8jDGUtR225PETgwjM8ZuA== [fileUNF]
Data generated and/or analysed in the Humanities and Social Sciences Communications article, "From language to meteorology: kinesis in weather events and weather verbs across Sinitic languages"
Sep 23, 2020
Puche, Adam, 2020, "Data for "National Institute of Health (NIH) grant awards: Does past performance predict future success?"", https://doi.org/10.7910/DVN/GECEVA, Harvard Dataverse, V1, UNF:6:4xKbrUNMGOdiceDkkJHbBw== [fileUNF]
Data for "National Institute of Health (NIH) grant awards: Does past performance predict future success?"
Sep 23, 2020
Moreno-Vera, Juan Ramón, 2020, "Concepts for historical and geographical thinking: qualitative analysis of Spanish and Swedish Primary Education curricula.", https://doi.org/10.7910/DVN/O3PDMW, Harvard Dataverse, V1
The original qualitative analysis for Spain's and Sweden's Primary Education curricula, using a evaluation table to research the presence of concepts for historical and geographical thinking in the Social Sciences subjects.
Sep 23, 2020
Kapitány-Fövény, Máté, 2020, "Replication Data for Kapitány-Fövény and Sulyok, 2020 "Social markers of a pandemic : modeling the association between cultural norms and COVID-19 spread data"", https://doi.org/10.7910/DVN/PRKEVU, Harvard Dataverse, V1, UNF:6:nEyYaeTshpTEA1XTOmylqg== [fileUNF]
Replication data/datasets (csv files) and statistical code (rmd file) for the manuscript "Social markers of a pandemic : modeling the association between cultural norms and COVID-19 spread data".
Jun 4, 2020
Cantante, Frederico, 2020, "Four profiles of inequality and tax redistribution in Europe", https://doi.org/10.7910/DVN/2TAQIO, Harvard Dataverse, V1, UNF:6:B+DM81kVzruk/+zLWqqZgw== [fileUNF]
Data on income inequality and tax redistribution in European countries.
Apr 8, 2020
Pykett, Jessica, 2020, "Data for 'Developing a Citizen Social Science approach to understand urban stress and promote wellbeing in urban communities'", https://doi.org/10.7910/DVN/D2FOTT, Harvard Dataverse, V1
Summary data for 31 participants of the 'Affective capture' project on the topic of urban stress, including World Health Organisation-Quality of Life-BREF and Perceived Stress Scale survey, biodata, participant diary, and researcher commentary on qualitative interviews.
Mar 30, 2020
Maciel Cardoso, Felipe, 2020, "Data and SI for: Understanding Drivers when Investing for Impact: an experimental study", https://doi.org/10.7910/DVN/G5ONIF, Harvard Dataverse, V1, UNF:6:d5xtIhj50a5DwW4V391gfw== [fileUNF]
[UNPUBLISHED] Experimental data for the paper "Understanding Drivers when Investing for Impact".
Dec 9, 2019
Yang, Kunhao; Fujisaki, Itsuki; Ueda, Kazuhiro, 2019, "Data for "Interplay of network structure and neighbour performance in user innovation"", https://doi.org/10.7910/DVN/ISRSDS, Harvard Dataverse, V1
Data Access for the paper "Interplay of network structure and neighbour performance in user innovation". Please see the README file for short description of the files in this repository.
Nov 11, 2019
Nguyen, Hoang, 2019, "Data and Supplementary Information for "The trilemma of sustainable industrial growth: Evidence from a piloting OECD’s Green city"", https://doi.org/10.7910/DVN/4BEQ0X, Harvard Dataverse, V1, UNF:6:bTvJy9AOqnCglMBN3zQtRg== [fileUNF]
Data of variables and Eviews 10 file for the relationship of industrial firm size and road infrastructure development with air pollution in Kitakyushu, Japan
Oct 14, 2019
Samantray, Abhishek; Pin, Paolo, 2019, "Data and code for: Credibility of climate change denial in social media", https://doi.org/10.7910/DVN/LNNPVD, Harvard Dataverse, V1
This repository contains data identifiers and code analyzed in the Palgrave Communications article "Credibility of climate change denial in social media" by Abhishek Samantray and Paolo Pin. Please see the README file for short description of the files in this repository.
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