placestats

Civil society participation vs. Gender score

Holds up after adjusting for income

Across 167 countries, Civil society participation and Gender score rise and fall together at r = +0.50 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = +0.47, q = 0.043, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of civil society participation, 0.502 to 0.827 points, gender score is better by 0.493 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.443 typical gaps.

Link before adjusting (r)+0.502p = 4.7e-12 · 167 countries
After adjusting for national income+0.469p = 1.9e-10 · likely range [+0.34, +0.58]
p, allowing for regions0.004standard error 0.102 · 7 regions
Check for luck (q)0.043across 12,497 pairs

How to read these.r runs from −1 (one goes up as the other goes down) to +1 (they rise together), and 0 means no link. Adjusting for national income means comparing countries with the same GDP per person, so differences in wealth can’t explain the link. Income is used in percentage terms, since an extra $1,000 means more to a poor country than to a rich one. p is how likely a link this strong would be if there were really none. Below 0.05 means it is unlikely to be chance. Very small values are written in short form: 1.1e-32 means a decimal point followed by 31 zeros and then 11, so very close to zero. The likely range is where the true figure probably lies, and a range that crosses zero means the link could easily be chance. Countries in the same region tend to resemble each other, so the third figure allows for that, which gives a fairer p. The standard error is the typical size of the error in r. Finally, testing this many pairs means some will look strong by luck alone. A q below 0.05 means this link is unlikely to be one of those.

Civil society participation · index (0-1)link with income +0.29 · independent
Gender score · typical gaps (standard deviations)link with income +0.37 · moderate

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Civil society participation · index (0-1) →Gender score · typical gaps (standard deviations) →0.0430.979-1.212.19Afghanistan: 0.043 index (0-1), -0.756 typical gaps (standard deviations)Angola: 0.433 index (0-1), 0.461 typical gaps (standard deviations)Albania: 0.595 index (0-1), 1.27 typical gaps (standard deviations)United Arab Emirates: 0.273 index (0-1), 0.89 typical gaps (standard deviations)Argentina: 0.707 index (0-1), 1.08 typical gaps (standard deviations)Armenia: 0.656 index (0-1), 1.26 typical gaps (standard deviations)Australia: 0.928 index (0-1), 1.57 typical gaps (standard deviations)Austria: 0.884 index (0-1), 1.17 typical gaps (standard deviations)Azerbaijan: 0.079 index (0-1), -0.374 typical gaps (standard deviations)Burundi: 0.314 index (0-1), 0.991 typical gaps (standard deviations)Belgium: 0.947 index (0-1), 1.45 typical gaps (standard deviations)Benin: 0.632 index (0-1), 0.759 typical gaps (standard deviations)Burkina Faso: 0.636 index (0-1), -0.093 typical gaps (standard deviations)Bangladesh: 0.696 index (0-1), -0.782 typical gaps (standard deviations)Bulgaria: 0.858 index (0-1), 0.273 typical gaps (standard deviations)Bahrain: 0.245 index (0-1), 0.0565 typical gaps (standard deviations)Bosnia and Herzegovina: 0.662 index (0-1), 0.116 typical gaps (standard deviations)Belarus: 0.112 index (0-1), 0.153 typical gaps (standard deviations)Bolivia: 0.845 index (0-1), 0.641 typical gaps (standard deviations)Brazil: 0.865 index (0-1), 0.685 typical gaps (standard deviations)Barbados: 0.896 index (0-1), 1.16 typical gaps (standard deviations)Bhutan: 0.694 index (0-1), -0.491 typical gaps (standard deviations)Botswana: 0.856 index (0-1), 0.25 typical gaps (standard deviations)Central African Republic: 0.337 index (0-1), -0.215 typical gaps (standard deviations)Canada: 0.938 index (0-1), 1.38 typical gaps (standard deviations)Switzerland: 0.971 index (0-1), 1.22 typical gaps (standard deviations)Chile: 0.775 index (0-1), 1.72 typical gaps (standard deviations)China: 0.219 index (0-1), -0.0629 typical gaps (standard deviations)Cote d'Ivoire: 0.707 index (0-1), 0.00107 typical gaps (standard deviations)Cameroon: 0.467 index (0-1), 0.739 typical gaps (standard deviations)Congo, Dem. Rep.: 0.515 index (0-1), -0.00209 typical gaps (standard deviations)Congo, Rep.: 0.566 index (0-1), -0.252 typical gaps (standard deviations)Colombia: 0.787 index (0-1), 0.908 typical gaps (standard deviations)Comoros: 0.545 index (0-1), -0.257 typical gaps (standard deviations)Cabo Verde: 0.683 index (0-1), 1.2 typical gaps (standard deviations)Costa Rica: 0.883 index (0-1), 1.7 typical gaps (standard deviations)Cyprus: 0.827 index (0-1), 0.593 typical gaps (standard deviations)Czechia: 0.777 index (0-1), 0.196 typical gaps (standard deviations)Germany: 0.979 index (0-1), 1.34 typical gaps (standard deviations)Djibouti: 0.439 index (0-1), 0.259 typical gaps (standard deviations)Denmark: 0.971 index (0-1), 1.1 typical gaps (standard deviations)Dominican Republic: 0.823 index (0-1), 1.32 typical gaps (standard deviations)Algeria: 0.302 index (0-1), -0.399 typical gaps (standard deviations)Ecuador: 0.69 index (0-1), 1.34 typical gaps (standard deviations)Egypt, Arab Rep.: 0.212 index (0-1), -0.204 typical gaps (standard deviations)Spain: 0.891 index (0-1), 1.69 typical gaps (standard deviations)Estonia: 0.89 index (0-1), 1.7 typical gaps (standard deviations)Ethiopia: 0.629 index (0-1), 1.4 typical gaps (standard deviations)Finland: 0.948 index (0-1), 2.04 typical gaps (standard deviations)Fiji: 0.846 index (0-1), -0.199 typical gaps (standard deviations)France: 0.866 index (0-1), 1.36 typical gaps (standard deviations)Gabon: 0.714 index (0-1), 0.419 typical gaps (standard deviations)United Kingdom: 0.889 index (0-1), 1.23 typical gaps (standard deviations)Georgia: 0.552 index (0-1), 0.641 typical gaps (standard deviations)Ghana: 0.893 index (0-1), 0.134 typical gaps (standard deviations)Guinea: 0.531 index (0-1), 0.289 typical gaps (standard deviations)Gambia, The: 0.8 index (0-1), 0.216 typical gaps (standard deviations)Guinea-Bissau: 0.78 index (0-1), -0.221 typical gaps (standard deviations)Equatorial Guinea: 0.099 index (0-1), -0.151 typical gaps (standard deviations)Greece: 0.752 index (0-1), 0.861 typical gaps (standard deviations)Guatemala: 0.761 index (0-1), 0.823 typical gaps (standard deviations)Guyana: 0.768 index (0-1), 1.29 typical gaps (standard deviations)Honduras: 0.754 index (0-1), 1.04 typical gaps (standard deviations)Croatia: 0.694 index (0-1), 0.51 typical gaps (standard deviations)Haiti: 0.478 index (0-1), -0.419 typical gaps (standard deviations)Hungary: 0.434 index (0-1), -0.00646 typical gaps (standard deviations)Indonesia: 0.711 index (0-1), 0.0942 typical gaps (standard deviations)India: 0.694 index (0-1), -0.409 typical gaps (standard deviations)Ireland: 0.954 index (0-1), 0.727 typical gaps (standard deviations)Iran, Islamic Rep.: 0.154 index (0-1), -0.961 typical gaps (standard deviations)Iraq: 0.697 index (0-1), 0.119 typical gaps (standard deviations)Iceland: 0.874 index (0-1), 2.19 typical gaps (standard deviations)Israel: 0.803 index (0-1), 0.453 typical gaps (standard deviations)Italy: 0.882 index (0-1), 0.707 typical gaps (standard deviations)Jamaica: 0.777 index (0-1), 1.09 typical gaps (standard deviations)Jordan: 0.646 index (0-1), -0.0146 typical gaps (standard deviations)Japan: 0.683 index (0-1), -0.021 typical gaps (standard deviations)Kazakhstan: 0.418 index (0-1), 0.296 typical gaps (standard deviations)Kenya: 0.718 index (0-1), 0.693 typical gaps (standard deviations)Kyrgyz Republic: 0.374 index (0-1), 0.129 typical gaps (standard deviations)Cambodia: 0.268 index (0-1), -0.47 typical gaps (standard deviations)Korea, Rep.: 0.804 index (0-1), 0.412 typical gaps (standard deviations)Kuwait: 0.473 index (0-1), -1.02 typical gaps (standard deviations)Lao PDR: 0.229 index (0-1), -0.093 typical gaps (standard deviations)Lebanon: 0.811 index (0-1), -0.687 typical gaps (standard deviations)Liberia: 0.899 index (0-1), 0.525 typical gaps (standard deviations)Libya: 0.631 index (0-1), -0.0625 typical gaps (standard deviations)Sri Lanka: 0.805 index (0-1), -0.262 typical gaps (standard deviations)Lesotho: 0.742 index (0-1), 0.261 typical gaps (standard deviations)Lithuania: 0.831 index (0-1), 0.944 typical gaps (standard deviations)Luxembourg: 0.954 index (0-1), 0.927 typical gaps (standard deviations)Latvia: 0.892 index (0-1), 1.32 typical gaps (standard deviations)Morocco: 0.651 index (0-1), 0.514 typical gaps (standard deviations)Moldova: 0.787 index (0-1), 1.45 typical gaps (standard deviations)Madagascar: 0.686 index (0-1), 0.668 typical gaps (standard deviations)Maldives: 0.662 index (0-1), -0.746 typical gaps (standard deviations)Mexico: 0.49 index (0-1), 1.33 typical gaps (standard deviations)North Macedonia: 0.541 index (0-1), 1.08 typical gaps (standard deviations)Mali: 0.7 index (0-1), 0.147 typical gaps (standard deviations)Malta: 0.82 index (0-1), 0.55 typical gaps (standard deviations)Myanmar: 0.128 index (0-1), 0.308 typical gaps (standard deviations)Montenegro: 0.708 index (0-1), 0.895 typical gaps (standard deviations)Mongolia: 0.677 index (0-1), 0.547 typical gaps (standard deviations)Mozambique: 0.705 index (0-1), 0.926 typical gaps (standard deviations)Mauritania: 0.63 index (0-1), 0.103 typical gaps (standard deviations)Mauritius: 0.854 index (0-1), 0.0843 typical gaps (standard deviations)Malawi: 0.931 index (0-1), 0.728 typical gaps (standard deviations)Malaysia: 0.755 index (0-1), -0.0868 typical gaps (standard deviations)Namibia: 0.667 index (0-1), 1.41 typical gaps (standard deviations)Niger: 0.82 index (0-1), 0.397 typical gaps (standard deviations)Nigeria: 0.786 index (0-1), -0.213 typical gaps (standard deviations)Nicaragua: 0.114 index (0-1), 1.98 typical gaps (standard deviations)Netherlands: 0.826 index (0-1), 1.19 typical gaps (standard deviations)Norway: 0.973 index (0-1), 1.53 typical gaps (standard deviations)Nepal: 0.858 index (0-1), 0.416 typical gaps (standard deviations)New Zealand: 0.656 index (0-1), 1.62 typical gaps (standard deviations)Oman: 0.318 index (0-1), -0.95 typical gaps (standard deviations)Pakistan: 0.651 index (0-1), -0.689 typical gaps (standard deviations)Panama: 0.632 index (0-1), 0.873 typical gaps (standard deviations)Peru: 0.706 index (0-1), 0.933 typical gaps (standard deviations)Philippines: 0.666 index (0-1), 0.494 typical gaps (standard deviations)Papua New Guinea: 0.604 index (0-1), -1.01 typical gaps (standard deviations)Poland: 0.729 index (0-1), 1.13 typical gaps (standard deviations)Portugal: 0.711 index (0-1), 1.05 typical gaps (standard deviations)Paraguay: 0.484 index (0-1), 0.39 typical gaps (standard deviations)Qatar: 0.181 index (0-1), -0.892 typical gaps (standard deviations)Romania: 0.656 index (0-1), 0.285 typical gaps (standard deviations)Russian Federation: 0.202 index (0-1), 0.137 typical gaps (standard deviations)Rwanda: 0.402 index (0-1), 1.02 typical gaps (standard deviations)Saudi Arabia: 0.25 index (0-1), -0.552 typical gaps (standard deviations)Sudan: 0.256 index (0-1), -1.21 typical gaps (standard deviations)Senegal: 0.874 index (0-1), 0.477 typical gaps (standard deviations)Singapore: 0.412 index (0-1), 1.04 typical gaps (standard deviations)Solomon Islands: 0.727 index (0-1), -0.473 typical gaps (standard deviations)Sierra Leone: 0.902 index (0-1), 0.991 typical gaps (standard deviations)El Salvador: 0.407 index (0-1), 0.618 typical gaps (standard deviations)Somalia, Fed. Rep.: 0.68 index (0-1), -0.615 typical gaps (standard deviations)Serbia: 0.525 index (0-1), 1.01 typical gaps (standard deviations)Sao Tome and Principe: 0.675 index (0-1), 0.8 typical gaps (standard deviations)Suriname: 0.829 index (0-1), 1.04 typical gaps (standard deviations)Slovak Republic: 0.662 index (0-1), 0.374 typical gaps (standard deviations)Slovenia: 0.907 index (0-1), 1.26 typical gaps (standard deviations)Sweden: 0.939 index (0-1), 1.79 typical gaps (standard deviations)Eswatini: 0.383 index (0-1), -0.0447 typical gaps (standard deviations)Seychelles: 0.858 index (0-1), 1.17 typical gaps (standard deviations)Syrian Arab Republic: 0.347 index (0-1), -0.767 typical gaps (standard deviations)Chad: 0.392 index (0-1), 0.144 typical gaps (standard deviations)Togo: 0.631 index (0-1), 0.48 typical gaps (standard deviations)Thailand: 0.641 index (0-1), 0.332 typical gaps (standard deviations)Tajikistan: 0.153 index (0-1), -0.106 typical gaps (standard deviations)Turkmenistan: 0.065 index (0-1), -0.394 typical gaps (standard deviations)Timor-Leste: 0.754 index (0-1), 0.73 typical gaps (standard deviations)Trinidad and Tobago: 0.907 index (0-1), 1.21 typical gaps (standard deviations)Tunisia: 0.478 index (0-1), 0.319 typical gaps (standard deviations)Turkiye: 0.355 index (0-1), -0.502 typical gaps (standard deviations)Tanzania: 0.793 index (0-1), 0.828 typical gaps (standard deviations)Uganda: 0.698 index (0-1), 0.849 typical gaps (standard deviations)Ukraine: 0.726 index (0-1), 0.643 typical gaps (standard deviations)Uruguay: 0.845 index (0-1), 0.63 typical gaps (standard deviations)United States: 0.963 index (0-1), 1.06 typical gaps (standard deviations)Uzbekistan: 0.344 index (0-1), 0.228 typical gaps (standard deviations)Viet Nam: 0.666 index (0-1), 0.0903 typical gaps (standard deviations)Vanuatu: 0.82 index (0-1), 0.107 typical gaps (standard deviations)Kosovo: 0.555 index (0-1), 0.375 typical gaps (standard deviations)South Africa: 0.776 index (0-1), 1.45 typical gaps (standard deviations)Zambia: 0.918 index (0-1), 0.211 typical gaps (standard deviations)Zimbabwe: 0.757 index (0-1), 0.576 typical gaps (standard deviations)AFGAREBDIBGDFINIRNISLLBNNICPNGSDNSWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5024.7e-12167
By rank (Spearman), not adjusted+0.5196.8e-13167
Standard (Pearson), adjusted for national income+0.4691.9e-10167
By rank (Spearman), adjusted for national income+0.4604.4e-10167

The rank version uses only each country’s place in line, from lowest to highest, so a few extreme countries count for less. The adjusted and unadjusted versions use the same 167 countries: those that report both measures and GDP per person. So the gap between them comes from the adjustment, not from a change in which countries are counted. Drop in the size of r after adjusting: +0.034 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.447 (without QAT) to +0.517 (without NIC). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: NIC (+0.049).

Fragile: this link may not hold up.
  • direction is not consistent across regions

Within each region

Countries are not separate, unrelated cases, and neighbors share a lot. A link that holds inside each region is far more believable than one that shows up only when comparing regions.

nr
East Asia & Pacific20+0.19
Europe & Central Asia49+0.69
Latin America & Caribbean23-0.20
Middle East, North Africa, Afghanistan & Pakistan21+0.42
Sub-Saharan Africa46+0.27

By income third

If the link shows up only in the richest third of countries, it is a feature of rich countries, not a general pattern.

nr
Poorest third56+0.19
Middle third55+0.45
Richest third56+0.69

By largest religious group

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
Christians99+0.26
Muslims48+0.36

By last european coloniser

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
France25+0.39
Never a European colony21+0.72
Spain19+0.12
United Kingdom49+0.46

Without outliers (countries far outside the middle half of countries on either measure, by more than one and a half times the width of that middle half): r = +0.469 after dropping 0 countries.

Two series, one country

Both measures over the years for one country you pick. The two charts are stacked so they share only the years along the bottom.

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Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.

The data


index (0-1)

typical gaps (standard deviations)
Years
Germany DEU0.9791.342025, 2024
Norway NOR0.9731.532025, 2024
Denmark DNK0.9711.12025, 2024
Switzerland CHE0.9711.222025
United States USA0.9631.062025
Luxembourg LUX0.9540.9272025, 2024
Ireland IRL0.9540.7272025, 2024
Finland FIN0.9482.042025, 2024
Belgium BEL0.9471.452025, 2024
Sweden SWE0.9391.792025, 2024
Canada CAN0.9381.382025, 2024
Malawi MWI0.9310.7282025, 2024
Australia AUS0.9281.572025, 2024
Zambia ZMB0.9180.2112025, 2024
Trinidad and Tobago TTO0.9071.212025, 2024

Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project
vdem; wb_gender; wdi

Sources

Civil society participation

Civil society participation index

V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual

How far governments consult civic groups, and how widely people take part in them. A part of the participatory democracy index.

Gender score

Gender score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 5 measures from 3 publishers. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Women's political empowerment, Women ministers, Women in parliament, Women in management, Married by 18.

How this was computed

Data used: most recent value in 2010-2025; values come from 2018–2025. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 7 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Civil society participation and Gender score

This page shows that two measures go together. It does not show that Civil society participation changes Gender score, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Civil society participation or Gender score