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Part 1: Document Description
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Citation |
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Title: |
Replication Data for: A Global Ranking of Research Productivity of Political Science Departments |
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Identification Number: |
doi:10.7910/DVN/JVSHQR |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2024-11-05 |
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Version: |
1 |
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Bibliographic Citation: |
Joan Barceló; Christopher Paik; Peter van der Windt; Zhai, Haoyu, 2024, "Replication Data for: A Global Ranking of Research Productivity of Political Science Departments", https://doi.org/10.7910/DVN/JVSHQR, Harvard Dataverse, V1 |
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Citation |
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Title: |
Replication Data for: A Global Ranking of Research Productivity of Political Science Departments |
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Identification Number: |
doi:10.7910/DVN/JVSHQR |
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Authoring Entity: |
Joan Barceló (New York University - Abu Dhabi) |
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Christopher Paik (New York University - Abu Dhabi) |
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Peter van der Windt (New York University - Abu Dhabi) |
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Zhai, Haoyu (New York University - Abu Dhabi) |
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Distributor: |
Harvard Dataverse |
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Access Authority: |
Zhai, Haoyu |
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Depositor: |
Zhai, Haoyu |
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Date of Deposit: |
2024-09-19 |
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Holdings Information: |
https://doi.org/10.7910/DVN/JVSHQR |
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Study Scope |
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Keywords: |
Social Sciences, Ranking, Global, Research Productivity |
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Abstract: |
This article provides a global ranking of research productivity of political science departments. We collect data on 115,427 articles and 12,696 books – written in both English and other languages – from 5,586 faculty members in 178 departments in Africa, Asia, Europe, Latin America and North America. Departments are ranked in terms of citations to articles published by faculty, impact factors of journals in which faculty published, and number of top publications in which faculty published. Results are presented for overall and more recent research productivity. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Label: |
Dataset_cleaned_Codebook.xlsx |
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Text: |
Codebook: Contains definitions for all variables in the cleaned datasets derived from the raw data. |
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Notes: |
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet |
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Label: |
Dataset_raw.RDS |
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Text: |
R Data File: Contains the raw dataset on political science department productivity worldwide, used in the analysis sequence. |
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Notes: |
application/gzip |
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Label: |
Dictionary_top_scholars.xlsx |
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Text: |
Spreadsheet File: Contains the regions where PhDs were conferred for top-ranked scholars in each region. |
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Notes: |
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet |
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Label: |
Dictionary_universities.xlsx |
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Text: |
Spreadsheet File: Contains full and abbreviated names of each university in the dataset. |
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Notes: |
application/vnd.openxmlformats-officedocument.spreadsheetml.sheet |
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Label: |
R_00_prepare_data.R |
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Text: |
Pre-processing Script (Step 0): Cleans the raw dataset, computes performance metrics, and produces three datasets for each level of analysis. |
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Notes: |
type/x-r-syntax |
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Label: |
R_01_compute_ranks.R |
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Text: |
Analysis Script (Step 1): Computes rankings and produces the main tables in the paper. |
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Notes: |
type/x-r-syntax |
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R_02_compute_extra.R |
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Analysis Script (Step 2): Computes statistics quoted in the main text and any additional graphs and tables in the paper. |
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Notes: |
type/x-r-syntax |
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R_03_include_status.R |
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Analysis Script (Step 3): Executes the final step of the analysis, replicating the main analysis by faculty status (academic rank). |
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Notes: |
type/x-r-syntax |
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R_master_run.R |
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Master Script: Oversees and automates the execution of all individual scripts (R_00*.R to R_03*.R) in a pipeline. |
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Notes: |
type/x-r-syntax |
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Label: |
_README.docx |
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Text: |
README Document: Instructions for replicating the analysis, including a description of the provided files. |
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Notes: |
application/vnd.openxmlformats-officedocument.wordprocessingml.document |