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Datasets:
cjerzak
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CountryRepresentationRankings

Modalities:
Tabular
Text
Formats:
csv
Size:
< 1K
Tags:
descriptive representation
political leadership
political science
social science
demographics
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pandas
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Country
stringlengths
4
27
Overall
float64
0.5
0.88
Representation Gap
float64
-0.27
-0.04
Ethnicity
float64
0.36
0.96
Gender
float64
0.56
0.83
Religion
float64
0.34
0.87
Language
float64
0.43
0.95
Iceland
0.88
-0.04
0.96
0.81
0.84
0.93
Poland
0.86
-0.08
0.96
0.69
0.87
0.93
Norway
0.86
-0.07
0.94
0.79
0.82
0.91
Denmark
0.86
-0.05
0.9
0.83
0.81
0.92
Finland
0.86
-0.05
0.91
0.81
0.84
0.87
Germany
0.85
-0.08
0.94
0.82
0.72
0.9
Armenia
0.84
-0.1
0.95
0.64
0.86
0.9
Portugal
0.84
-0.09
0.95
0.73
0.75
0.91
Tunisia
0.83
-0.1
0.95
0.69
0.8
0.88
Madagascar
0.83
-0.08
0.91
0.7
0.81
0.9
Sweden
0.83
-0.06
0.87
0.82
0.76
0.85
Qatar
0.83
-0.08
0.94
0.76
0.79
0.81
Malta
0.82
-0.08
0.92
0.67
0.83
0.87
Croatia
0.82
-0.09
0.89
0.75
0.74
0.89
Jordan
0.81
-0.12
0.87
0.62
0.86
0.9
Greece
0.81
-0.12
0.89
0.69
0.8
0.87
China, People's Republic of
0.81
-0.12
0.96
0.63
0.71
0.95
Bangladesh
0.81
-0.1
0.92
0.74
0.75
0.84
Serbia
0.81
-0.08
0.85
0.72
0.8
0.87
Yemen
0.81
-0.12
0.87
0.72
0.78
0.87
Jamaica
0.81
-0.1
0.89
0.77
0.69
0.89
France
0.81
-0.11
0.9
0.73
0.71
0.89
Egypt
0.81
-0.12
0.91
0.63
0.82
0.86
Somaliland
0.81
-0.09
0.93
0.65
0.78
0.87
Thailand
0.8
-0.12
0.9
0.61
0.81
0.89
Costa Rica
0.8
-0.09
0.86
0.73
0.75
0.85
Puerto Rico
0.8
-0.08
0.8
0.69
0.77
0.93
Italy
0.79
-0.13
0.9
0.68
0.71
0.88
Colombia
0.79
-0.1
0.86
0.69
0.72
0.89
Korea, South
0.79
-0.12
0.94
0.64
0.67
0.9
Ireland
0.79
-0.11
0.83
0.69
0.74
0.89
Honduras
0.79
-0.11
0.87
0.67
0.76
0.86
Slovakia
0.78
-0.12
0.91
0.68
0.7
0.84
Burundi
0.78
-0.09
0.82
0.71
0.7
0.88
United Kingdom
0.78
-0.13
0.89
0.65
0.66
0.91
Japan
0.78
-0.13
0.94
0.62
0.63
0.92
Netherlands
0.78
-0.08
0.79
0.76
0.68
0.87
Cambodia
0.77
-0.14
0.86
0.66
0.78
0.8
Romania
0.77
-0.14
0.84
0.73
0.73
0.79
Uruguay
0.77
-0.11
0.85
0.68
0.68
0.88
Korea, North
0.77
-0.14
0.89
0.64
0.7
0.85
Czech Republic
0.77
-0.15
0.83
0.65
0.7
0.9
Bulgaria
0.77
-0.13
0.85
0.7
0.73
0.8
Turkmenistan
0.77
-0.15
0.82
0.64
0.83
0.78
El Salvador
0.76
-0.11
0.86
0.66
0.68
0.86
Saudi Arabia
0.76
-0.14
0.81
0.65
0.74
0.85
Russian Federation
0.76
-0.16
0.84
0.63
0.69
0.89
Nicaragua
0.76
-0.1
0.73
0.75
0.71
0.86
Djibouti
0.76
-0.06
0.79
0.66
0.86
0.74
Palestinian Territory
0.76
-0.14
0.8
0.61
0.77
0.86
Slovenia
0.76
-0.12
0.83
0.7
0.69
0.82
South Africa
0.76
-0.07
0.85
0.74
0.74
0.71
Cape Verde
0.76
-0.14
0.73
0.71
0.74
0.85
Turkey
0.76
-0.14
0.79
0.62
0.81
0.82
Lesotho
0.76
-0.12
0.94
0.63
0.62
0.83
Zimbabwe
0.76
-0.13
0.79
0.71
0.74
0.78
Hungary
0.75
-0.16
0.9
0.57
0.65
0.91
Viet Nam
0.75
-0.16
0.88
0.65
0.68
0.8
Azerbaijan
0.75
-0.14
0.84
0.65
0.68
0.83
Kyrgyzstan
0.75
-0.13
0.77
0.73
0.8
0.7
Kosovo
0.75
-0.16
0.89
0.73
0.57
0.81
New Zealand
0.75
-0.09
0.72
0.76
0.67
0.84
Kuwait
0.75
-0.16
0.81
0.67
0.69
0.83
Georgia
0.75
-0.12
0.84
0.66
0.78
0.72
Libya
0.75
-0.14
0.77
0.65
0.73
0.83
Macedonia
0.75
-0.09
0.78
0.74
0.71
0.75
Rwanda
0.74
-0.13
0.71
0.79
0.67
0.81
Cyprus
0.74
-0.13
0.8
0.68
0.69
0.8
Angola
0.74
-0.13
0.73
0.73
0.71
0.78
Haiti
0.74
-0.16
0.85
0.63
0.68
0.79
Mexico
0.74
-0.17
0.68
0.66
0.7
0.9
Spain
0.73
-0.12
0.74
0.71
0.71
0.77
Uzbekistan
0.73
-0.17
0.84
0.63
0.69
0.76
Switzerland
0.73
-0.13
0.76
0.74
0.69
0.74
Cuba
0.73
-0.18
0.71
0.75
0.62
0.84
Syria
0.73
-0.17
0.78
0.69
0.7
0.75
Lithuania
0.73
-0.15
0.82
0.74
0.58
0.79
Somalia
0.73
-0.15
0.8
0.65
0.69
0.77
Singapore
0.73
-0.11
0.8
0.74
0.67
0.7
Iraq
0.73
-0.18
0.78
0.68
0.7
0.74
Suriname
0.73
-0.16
0.71
0.69
0.68
0.82
Montenegro
0.72
-0.12
0.69
0.67
0.72
0.82
Venezuela
0.72
-0.16
0.61
0.66
0.75
0.88
Mongolia
0.72
-0.17
0.73
0.67
0.69
0.8
Moldova, Republic of
0.72
-0.13
0.76
0.68
0.74
0.72
Belgium
0.72
-0.12
0.75
0.7
0.69
0.74
Philippines
0.72
-0.12
0.84
0.67
0.77
0.61
Oman
0.72
-0.17
0.75
0.71
0.72
0.72
United Arab Emirates
0.72
-0.18
0.82
0.74
0.74
0.59
Albania
0.72
-0.19
0.9
0.65
0.47
0.85
Nepal
0.72
-0.17
0.72
0.7
0.74
0.7
Afghanistan
0.71
-0.1
0.72
0.65
0.78
0.7
Trinidad and Tobago
0.71
-0.16
0.72
0.73
0.67
0.72
Ecuador
0.71
-0.16
0.63
0.7
0.74
0.77
Pakistan
0.71
-0.15
0.68
0.62
0.81
0.72
China, Republic of
0.71
-0.2
0.58
0.74
0.66
0.84
Bolivia
0.71
-0.14
0.57
0.77
0.68
0.81
Ukraine
0.7
-0.19
0.8
0.59
0.67
0.75
Timor-Leste
0.7
-0.19
0.62
0.69
0.85
0.66
Algeria
0.7
-0.19
0.67
0.64
0.85
0.64
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Country Representation Rankings

Filename: CountryRepresentationRankings.csv

This dataset is part of the Global Leadership Project (GLP) 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 [.bib]
@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}
}
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