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Data

Lesbian, gay, and bisexual people allowed to openly serve in the military

See all data and research on:
LGBT+ RightsHuman Rights

What you should know about this indicator

The indicator is coded as follows: Allowed (LGB people are allowed to serve in the military), No policy (there is no policy allowing nor banning LGB military service) and Banned (LGB people are banned to serve in the military).

Lesbian, gay, and bisexual people allowed to openly serve in the military
Measures if lesbian, gay, and bisexual people are allowed or banned to serve in the military.
Source
Velasco (2020) – with major processing by Our World in Data
Last updated
April 27, 2023
Date range
1991–2019

Sources and processing

This data is based on the following sources

Velasco – LGBT+ policies (Kristopher Velasco)

Velasco measures a country’s LGBT+ policy landscape with an original LGBT+ policy index that he created; the LGBT+ Policy Index captures the implementation of 18 different LGBT+ policies. Policies included in the index are limited to those adopted across at least three countries or are explicitly advocated for by transnational activists.

These policies are subdivided between:

Progressive policies: 1. Same-Sex Sexual Acts Legal 2. Equal Age of Consent 3. Employment Discrimination 4. Hate Crime Protections 5. Incitement to Hatred 6. Civil Unions 7. Marriage Equality 8. Joint Adoptions 9. Gender Marker Change 10. LGB Military 11. Transgender Military 12. Ban on Conversion Therapies 13. Ban on Gender Assignment Surgeries on Children

Regressive policies 1. Death Penalty for Same-Sex Sexual Acts 2. Propaganda Laws 3. Same-Sex Sexual Acts Illegal 4. Unequal Age of Consent 5. Ban on Marriage Equality

These policies are not measured in a binary (adopted/not-adopted) scheme; the author follows Frank and colleagues (2010, 2017) in considering that similar policies can meaningfully vary in scope, benefits, punishment, etc. So, he determines the robustness of each policy by reviewing five indicators (between parentheses are the scoring schemes):

  1. Proportion of Population Living Under Law: To acknowledge subnational variations (0-1)
  2. Scope of Genders Subject to Law: As they can be typically differentiated by gender (0: no law, 0.5: just men or women, 1: both)
  3. Maximum Level of Punishment: For regressive policies (0: no law, 0.2: <3 years, 0.4: >3 years and <15 years, 0.6: >15 years and < life, 0.8: live in prison, 1: death penalty)
  4. Ease of Access: To benefits the law outlines (0: no law, 0.25: significant barriers, 0.5: moderate barriers, 0.75: little to few barriers, 1: no barriers)
  5. Evidence of Enforcement: Has been least one case the previous year where this was implemented? (0: no evidence, 1: evidence)

While all five indicators may not be relevant to each policy, each policy in question uses at least three different indicators and with them, each policy score ranges from 0 to 1. Therefore, a score of 1 corresponds to that policy's most robust scope and implementation. This also means that changes in any indicators will influence each policy’s overall score. For example, a country having national marriage equality (indicator 1), few (if any) formal restrictions to obtaining a marriage license (indicator 4), and full implementation (indicator 5) will receive a score of 1.

To create the index, the scores for each policy are summed together annually, with progressive policies receiving a positive score and regressive policies receiving a negative. This results in an index ranging from -5 to +13. No country reaches these extremes, demonstrating that countries can get better and worse in their policy environments.

The LGBT+ policy index represents the most robust and nuanced measure of LGBT+ policy adoption and implementation to date and is a novel contribution to the literature. By incorporating progressive and regressive LGBT+ policies and variation in implementation beyond a binary coding scheme, this measure captures even fine-grained changes to the LGBT+ policy landscape. It better assesses the extent to which countries are or are not influenced by transnational processes.

Multiple sources were consulted to find the necessary data to construct this index. The primary data source was the State Sponsored Homophobia Reports produced by ILGA. These reports, produced almost annually, outline the adoption of various policies and provide some information on implementation. For information on trans- and intersex-specific policies and military information, other sources were used, including the Trans Legal Mapping Report, also produced by ILGA, reports and documentation provided by Transgender Europe, Movement Advancement Project, The Hague Center for Strategic Studies LGBT+ Military Index, and academic studies such as Reynolds (2013). Furthermore, multiple sources were used to obtain data on the evidence of enforcement – particularly arrests – including an extensive newspaper search across each country using LexisNexis and Factiva and other external reports by Amnesty International, Human Rights Watch, and the U.S. State Department.

Retrieved on
June 15, 2023
Retrieved from
https://osf.io/preprints/socarxiv/3rtje/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Velasco, K. (2020). Transnational Backlash and the Deinstitutionalization of Liberal Norms: LGBT+ Rights in a Contested World. https://doi.org/10.31235/osf.io/3rtje

Velasco measures a country’s LGBT+ policy landscape with an original LGBT+ policy index that he created; the LGBT+ Policy Index captures the implementation of 18 different LGBT+ policies. Policies included in the index are limited to those adopted across at least three countries or are explicitly advocated for by transnational activists.

These policies are subdivided between:

Progressive policies: 1. Same-Sex Sexual Acts Legal 2. Equal Age of Consent 3. Employment Discrimination 4. Hate Crime Protections 5. Incitement to Hatred 6. Civil Unions 7. Marriage Equality 8. Joint Adoptions 9. Gender Marker Change 10. LGB Military 11. Transgender Military 12. Ban on Conversion Therapies 13. Ban on Gender Assignment Surgeries on Children

Regressive policies 1. Death Penalty for Same-Sex Sexual Acts 2. Propaganda Laws 3. Same-Sex Sexual Acts Illegal 4. Unequal Age of Consent 5. Ban on Marriage Equality

These policies are not measured in a binary (adopted/not-adopted) scheme; the author follows Frank and colleagues (2010, 2017) in considering that similar policies can meaningfully vary in scope, benefits, punishment, etc. So, he determines the robustness of each policy by reviewing five indicators (between parentheses are the scoring schemes):

  1. Proportion of Population Living Under Law: To acknowledge subnational variations (0-1)
  2. Scope of Genders Subject to Law: As they can be typically differentiated by gender (0: no law, 0.5: just men or women, 1: both)
  3. Maximum Level of Punishment: For regressive policies (0: no law, 0.2: <3 years, 0.4: >3 years and <15 years, 0.6: >15 years and < life, 0.8: live in prison, 1: death penalty)
  4. Ease of Access: To benefits the law outlines (0: no law, 0.25: significant barriers, 0.5: moderate barriers, 0.75: little to few barriers, 1: no barriers)
  5. Evidence of Enforcement: Has been least one case the previous year where this was implemented? (0: no evidence, 1: evidence)

While all five indicators may not be relevant to each policy, each policy in question uses at least three different indicators and with them, each policy score ranges from 0 to 1. Therefore, a score of 1 corresponds to that policy's most robust scope and implementation. This also means that changes in any indicators will influence each policy’s overall score. For example, a country having national marriage equality (indicator 1), few (if any) formal restrictions to obtaining a marriage license (indicator 4), and full implementation (indicator 5) will receive a score of 1.

To create the index, the scores for each policy are summed together annually, with progressive policies receiving a positive score and regressive policies receiving a negative. This results in an index ranging from -5 to +13. No country reaches these extremes, demonstrating that countries can get better and worse in their policy environments.

The LGBT+ policy index represents the most robust and nuanced measure of LGBT+ policy adoption and implementation to date and is a novel contribution to the literature. By incorporating progressive and regressive LGBT+ policies and variation in implementation beyond a binary coding scheme, this measure captures even fine-grained changes to the LGBT+ policy landscape. It better assesses the extent to which countries are or are not influenced by transnational processes.

Multiple sources were consulted to find the necessary data to construct this index. The primary data source was the State Sponsored Homophobia Reports produced by ILGA. These reports, produced almost annually, outline the adoption of various policies and provide some information on implementation. For information on trans- and intersex-specific policies and military information, other sources were used, including the Trans Legal Mapping Report, also produced by ILGA, reports and documentation provided by Transgender Europe, Movement Advancement Project, The Hague Center for Strategic Studies LGBT+ Military Index, and academic studies such as Reynolds (2013). Furthermore, multiple sources were used to obtain data on the evidence of enforcement – particularly arrests – including an extensive newspaper search across each country using LexisNexis and Factiva and other external reports by Amnesty International, Human Rights Watch, and the U.S. State Department.

Retrieved on
June 15, 2023
Retrieved from
https://osf.io/preprints/socarxiv/3rtje/
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Velasco, K. (2020). Transnational Backlash and the Deinstitutionalization of Liberal Norms: LGBT+ Rights in a Contested World. https://doi.org/10.31235/osf.io/3rtje

How we process data at Our World in Data

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline
Notes on our processing step for this indicator

We estimated regional aggregations by using Our World in Data definitions of regions and our consolidated population data.

From the original dataset, we combined data from two different indicators: LGB allowed in military and LGB military ban.

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Citations

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Lesbian, gay, and bisexual people allowed to openly serve in the military”, part of the following publication: Bastian Herre and Pablo Arriagada (2023) - “LGBT+ Rights”. Data adapted from Velasco. Retrieved from https://archive.ourworldindata.org/20260304-094028/grapher/lgb-military-velasco.html [online resource] (archived on March 4, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Velasco (2020) – with major processing by Our World in Data

Full citation

Velasco (2020) – with major processing by Our World in Data. “Lesbian, gay, and bisexual people allowed to openly serve in the military” [dataset]. Velasco, “LGBT+ policies (Kristopher Velasco)” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260304-094028/grapher/lgb-military-velasco.html (archived on March 4, 2026).

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Data URL (CSV format)
https://ourworldindata.org/grapher/lgb-military-velasco.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/lgb-military-velasco.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/lgb-military-velasco.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/lgb-military-velasco.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/lgb-military-velasco.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/lgb-military-velasco.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/lgb-military-velasco.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/lgb-military-velasco.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear