--- title: "Country Representation Rankings" sdk: "datasets" taskCategories: - "research" tags: - "descriptive representation" - "political leadership" - "political science" - "social science" - "demographics" license: "mit" datasets: - "CountryRepresentationRankings.csv" --- # Country Representation Rankings **Filename**: `CountryRepresentationRankings.csv` This dataset is part of the [Global Leadership Project (GLP)](https://globalleadershipproject.net/) and presents a set of indices measuring how closely a country’s political leadership reflects the demographic characteristics of its population. --- ## Context The .csv source provides: - **Overall**: An overall representation index. Higher (positive) scores suggest political leadership is more demographically similar to the general population, while more negative scores imply greater shortfalls in representation. - **Representation Gap**: The difference between the observed levels of representation and what would be expected under a random selection model. - **Ethnicity, Gender, Religion, Language**: Specific representation indices broken down by group type. **Note**: Because some observations did not meet our 75% completeness threshold, we used an imputation algorithm for missing data. Values should be interpreted with caution. For full details on how the data was collected and how each index was computed, please refer to the accompanying paper. --- ## Dataset Structure Each row corresponds to a country and contains: | **Column** | **Description** | |------------------------|-------------------------------------------------------------------------------------------------------------------------------------| | `Country` | Country name | | `Overall` | Overall representation index | | `Representation Gap` | Gap between observed and expected representation levels | | `Ethnicity` | Representation index for ethnic groups | | `Gender` | Representation index by gender | | `Religion` | Representation index for religious groups | | `Language` | Representation index for language groups | --- ## Usage Researchers and policymakers can use these metrics to: - Compare levels of demographic representation across countries. - Identify areas where representation may be lacking (e.g., by gender or religion). - Track changes in representation indices over time if multiple data snapshots are available. --- ## Methodological Notes - **Data Imputation**: Some entries were imputed when countries did not meet the 75% completeness threshold. - **Interpretation**: The indices are constructed relative to population demographics; a score near 1 indicates close parity between leaders and population groups, while scores closer to 0 or negative values suggest underrepresentation. --- ## Citation If you use this dataset, please cite the following paper: - Gerring, John, Connor T. Jerzak, and Erzen Öncel. 2024. “The Composition of Descriptive Representation.” *American Political Science Review* 118(2): 784–801. [PDF](https://www.cambridge.org/core/services/aop-cambridge-core/content/view/7EAEA1CA4C553AB9D76054D1FA9C0840/S0003055423000680a.pdf/the-composition-of-descriptive-representation.pdf) [[.bib]](https://connorjerzak.com/wp-content/uploads/2024/07/CompositionBib.txt) ``` @article{Gerring2024Composition, title={The Composition of Descriptive Representation}, author={Gerring, John and Jerzak, Connor T. and Öncel, Erzen}, journal={American Political Science Review}, year={2024}, volume={118}, number={2}, pages={784--801}, url={https://www.cambridge.org/core/services/aop-cambridge-core/content/view/7EAEA1CA4C553AB9D76054D1FA9C0840/S0003055423000680a.pdf/the-composition-of-descriptive-representation.pdf} } ``` ---