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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: Policy Networks Across Political Systems |
Identification Number: |
doi:10.7910/DVN/NKCDCO |
Distributor: |
Harvard Dataverse |
Date of Distribution: |
2022-01-04 |
Version: |
1 |
Bibliographic Citation: |
Metz, Florence; Brandenberger, Laurence, 2022, "Replication Data for: Policy Networks Across Political Systems", https://doi.org/10.7910/DVN/NKCDCO, Harvard Dataverse, V1 |
Citation |
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Title: |
Replication Data for: Policy Networks Across Political Systems |
Identification Number: |
doi:10.7910/DVN/NKCDCO |
Authoring Entity: |
Metz, Florence (University of Twente) |
Brandenberger, Laurence (ETH Zurich) |
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Producer: |
Laurence Brandenberger |
Distributor: |
Harvard Dataverse |
Access Authority: |
Brandenberger, Laurence |
Depositor: |
Brandenberger, Laurence |
Date of Deposit: |
2021-03-01 |
Holdings Information: |
https://doi.org/10.7910/DVN/NKCDCO |
Study Scope |
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Keywords: |
Social Sciences, Social Sciences, Political networks, Political systems, Comparative politics, Inferential network analysis |
Abstract: |
Polities shape power structures and interaction patterns between actors in policymaking processes. Although the social fabric of interactions is key to successful policymaking, it remains unclear which relational structures are typically found across political systems. By adopting a network approach, we analyze differences in power structures and interac- tion patterns across four policy networks in German and Swiss consensual-federal, French majoritarian-unitary, and hybrid Dutch consensual-unitary democracies. Using survey data from 149 state and non-state actors, we fit exponential random graph models and calcu- late predicted probabilities to compare the four networks. Results show that the consen- sus democracies institutionalize neighborhoods of networks where actors share power and collaborate with opponents. Our case of a majoritarian democracy illustrates power con- centration with restricted access to competitors, limiting the need to interact and search for compromises with opponents. Findings allow future work to differentiate typical from atypical network structures, given the embeddedness into a political system. |
Notes: |
This dataset underwent an independent verification process that replicated the tables and figures in the primary article. For the supplementary materials, verification was performed solely for the successful execution of code. The verification process was carried out by the Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. <br></br> The associated article has been awarded Open Materials and Open Data Badges. Learn more about the Open Practice Badges from the <a href="https://osf.io/tvyxz/wiki/home/" target="_blank">Center for Open Science</a>.<br></br> <img src="https://odum.unc.edu/files/2020/03/OpenData_PR-1.png" alt="Open Data Badge" height="77" width="80"> <img src="https://odum.unc.edu/files/2020/03/OpenMaterials_PR-1.png" alt="Open Materials Badge" height="77" width="80"> |
Methodology and Processing |
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Sources Statement |
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Data Access |
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Disclaimer: |
The <i>American Journal of Political Science</i> and the Odum Institute for Research in Social Science are not responsible for the accuracy or quality of data uploaded within the <i>AJPS</i> Dataverse, for the use of those data, or for interpretations or conclusions based on their use. |
Other Study Description Materials |
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Related Publications |
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Citation |
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Bibliographic Citation: |
Metz, Florence and Laurence Brandenberger. [date]. "Policy Networks Across Political Systems." <i>American Journal of Political Science</i> Forthcoming. <a href="http://ajps.org/" target="_blank">http://ajps.org/</a> |
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attributeData.RData |
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R data frame containing attribute data for every policy network. |
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application/x-rlang-transport |
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Codebook_MetzBrandenberger2021.pdf |
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Codebook for the data. |
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application/pdf |
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coordinates_nwplots.RData |
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R data frame containing coordinates for the network plots to facilitate exact replication |
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application/x-rlang-transport |
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dataoutput_full.RData |
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R data frame containing the final output, including processed data, ERGMs, GOFs, etc. |
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application/x-rlang-transport |
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data_prepared.RData |
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RData-file containing raw data |
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application/x-rlang-transport |
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edgeprobabilities.RData |
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R data frame containing edge probabilities |
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application/x-rlang-transport |
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FIG1_nw_collab_plusbar.pdf |
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Figure 1 in the article, PDF format |
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application/pdf |
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FIG2_fit_ergmint.pdf |
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Figure 2 in the article, PDF format |
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application/pdf |
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FIG3_ERGM_interaction.pdf |
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Figure 3 in the article, PDF format |
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application/pdf |
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FIG4_popularity_relative_full.pdf |
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Figure 4 in the article, PDF format |
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application/pdf |
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FIG5_prOpponentsOnly_relative_noFR.pdf |
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Figure 5 in the article, PDF format |
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application/pdf |
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FIG6_belief_boxplot_predpr_relative_FRonly.pdf |
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Figure 6 in the article, PDF format |
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application/pdf |
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fit1CHb.RData |
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ERGM output, Swiss policy network, no interaction, alternative specification |
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application/x-rlang-transport |
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fit1CH.RData |
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ERGM output, Swiss policy network, no interaction |
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application/x-rlang-transport |
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fit1DE.RData |
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ERGM output, German policy network, no interaction |
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application/x-rlang-transport |
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fit1FR.RData |
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ERGM output, French policy network, no interaction |
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application/x-rlang-transport |
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fit1NL.RData |
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ERGM output, Dutch policy network, no interaction |
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application/x-rlang-transport |
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fit2CH_10.RData |
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ERGM output, Swiss policy network, robustness check missing data, 10% missing |
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application/x-rlang-transport |
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fit2CH_20.RData |
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ERGM output, Swiss policy network, robustness check missing data, 20% missing |
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application/x-rlang-transport |
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fit2CH_30.RData |
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ERGM output, Swiss policy network, robustness check missing data, 30% missing |
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application/x-rlang-transport |
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fit2CH_40.RData |
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ERGM output, Swiss policy network, robustness check missing data, 40% missing |
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application/x-rlang-transport |
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fit2CH.RData |
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ERGM output, Swiss policy network, with interaction |
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application/x-rlang-transport |
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fit2DE.RData |
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ERGM output, German policy network, with interaction |
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application/x-rlang-transport |
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fit2FR.RData |
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ERGM output, French policy network, with interaction |
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application/x-rlang-transport |
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fit2NL.RData |
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ERGM output, Dutch policy network, with interaction |
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application/x-rlang-transport |
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full_script.R |
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full R script |
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type/x-r-syntax |
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InterpretationFunctions_Desmarais_Cranmer_2012.R |
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R script with interpretation function for predicted probabilities |
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type/x-r-syntax |
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README_ReplicationMaterial.md |
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read me file (md) |
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text/markdown |
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README_ReplicationMaterial.pdf |
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read me file (pdf, for easy reading) |
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application/pdf |
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README_ReplicationMaterial.txt |
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read me file (txt) |
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text/plain |
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SIFIG1_nw_collabOpponents_all.pdf |
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Figure 1 in the SI Online, PDF format |
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application/pdf |
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SIFIG2_beliefsim_namedasopponents.pdf |
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Figure 2 in the SI Online, PDF format |
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application/pdf |
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SIFIG3_fit_ergm_gof_CH_appendix.pdf |
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Figure 3 in the SI Online, PDF format |
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application/pdf |
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SIFIG4_prOpponents_Gov_relative.pdf |
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Figure 4 in the SI Online, PDF format |
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application/pdf |
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SIFIG5_instrument_boxplot_predpr_relative.pdf |
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Figure 5 in the SI Online, PDF format |
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application/pdf |
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SIFIG6_boxplot_missingObs_Reputation.pdf |
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Figure 6 in the SI Online, PDF format |
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application/pdf |
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SITAB3_ergms_interaction.tex |
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Table 3 in the SI Online, PDF format |
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application/x-tex |
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SITAB4_ergms.tex |
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Table 4 in the SI Online, PDF format |
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application/x-tex |
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SITAB5_ergms_CHonly.tex |
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Table 5 in the SI Online, PDF format |
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application/x-tex |
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SITAB6_ergms_missingObs.tex |
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Table 6 in the SI Online, PDF format |
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application/x-tex |