Based on assessment of the de facto protection of academic freedom as of December 2022, the Academic Freedom Index Update 2023 provides an overview of the state of academic freedom in 179 countries and territories. Academic freedom is in retreat for over 50% of the world’s population – 4 billion people. This year’s update of the AFI identifies 22 countries and territories where universities and scholars enjoy significantly less freedom today than 10 years ago. During the same period, academic freedom has improved in only five small countries, which benefits a mere 0.7% of the global population. Academic freedom is stagnating in most countries (152), often at far too low a level.
The Academic Freedom Index (AFI) is a unique approach to conceptualizing and measuring academic freedom. It assesses de facto levels of academic freedom around the world based on five indicators: freedom to research and teach ; freedom of academic exchange and dissemination ; institutional autonomy ; campus integrity ; and freedom of academic and cultural expression .
To learn more about the current state of academic freedom worldwide, read the update of the Academic Freedom Index and explore the data in our interactive world map.
The Academic Freedom Index (AFI) covers 179 countries and territories, and provides the most comprehensive dataset on the subject of academic freedom to date. It rests on assessments by 2,197 country experts worldwide, standardized questionnaires, and a well-established statistical model, implemented and adapted by the V-Dem project. The V-Dem project is known for generating sound data on various dimensions of democracy. The Academic Freedom Index uses this method for data aggregation: it not only provides so-called point estimates, but also transparently reports measurement uncertainty in the global assessment of academic freedom. We strongly recommend that users take this uncertainty into account when comparing scores between countries and over time
AFI data rests on assessments by country experts with different backgrounds and expertise. V-Dem has developed an innovative method for aggregating expert judgments that produces valid and reliable estimates of difficult-to-observe concepts, such as academic freedom and democracy. This aspect of the project is critical because many key features of academic freedom are not directly observable. We continually review our methodology – and make occasional adjustments – to improve the quality of our indicators and the AFI.
The AFI typically gathers data from more than five experts per country-year observation, using a pool of 2,197 country experts who provide judgment on different indicators and cases. Experts hail from almost every country in the world, allowing us to leverage diverse expertise and knowledge. To learn more about the AFI please use this introduction:
Spannagel, J., & Kinzelbach, K. (2022). The Academic Freedom Index and its indicators: Introduction to new global time-series V-Dem data. Quality & Quantity. https://doi.org/10.1007/s11135-022-01544-0
Even though expert-coded data is valuable for assessing academic freedom across countries and time, it poses multiple problems: The way experts rate academic freedom and its indicators differs between experts and cases and time. To address these issues, we use the V-Dem’s customized item response theory (IRT) measurement model. This IRT model helps us account for uncertainty about estimates and potential biases.
The V-Dem measurement model assumes that there are concepts that we can’t directly observe, like the level of academic freedom. Instead, we can only assess imperfect versions of this concept in the form of the ratings that experts give. V-Dem’s IRT model takes these ratings and converts them into a single continuous latent scale.
The IRT model also calculates how reliable each expert is in comparison to others, as well as how their rating scales may differ from those of other experts. It also uses overlapping coding (some experts code multiple countries) and all experts code hypothetical cases – so-called anchoring vignettes – to estimate the degree to which differences in scale perception are systematic across experts who code different sets of cases.
In the resulting V-Dem dataset, we present users with a best estimate of the value for a country-year score (the point estimate), as well as an uncertainty estimate (the credible regions, a Bayesian corollary of confidence intervals). In addition, the interval-level estimates provided by the dataset can be hard for some users to understand in practical terms. To help with this, the AFI also offers interval-level point estimates that have been transformed back to the original coding scale used by the experts, which ranges from 0 to 4. For more information on how to interpret the data, users can refer to the V-Dem codebook. Finally, we also provide ordinal versions of each variable for users who need ordered categorical values. Both the transformed point estimates and the ordinal versions come with credible regions to provide users with a sense of the estimate’s accuracy.
To learn more about the data generation process and the V-Dem methodology, read the working paper on the V-Dem measurement model, as well as the methodology FAQ at V-Dem’s website.
Here you can find peer-reviewed publications and other material from the AFI Team about the Academic Freedom Index.
- Spannagel, J., & Kinzelbach, K. (2022). The Academic Freedom Index and its indicators: Introduction to new global time-series V-Dem data. Quality & Quantity. https://doi.org/10.1007/s11135-022-01544-0
- Pelke, L., & Spannagel, J. (2023). Quality Assessment of the Academic Freedom Index: Strengths, Weaknesses, and How Best to Use It. V-Dem Working Papers Series 2023:142. https://v-dem.net/media/publications/wp_142.pdf
- Kinzelbach, K., Lindberg, S. I., Pelke, L., & Spannagel, J. (2023). Academic Freedom Index – 2023 Update. https://doi.org/10.25593/opus4-fau-21630
- Kinzelbach, K., Lindberg, S. I., Pelke, L., & Spannagel, J. (2022). Academic Freedom Index – 2022 Update. https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/18612
- Kinzelbach, K., Saliba, I., & Spannagel, J. (2022). Global data on the freedom indispensable for scientific research: Towards a reconciliation of academic reputation and academic freedom. The International Journal of Human Rights, 26 (10), 1723–1740. https://doi.org/10.1080/13642987.2021.1998000
- Kinzelbach, K., Saliba, I., Spannagel, J., & Quinn, R. (2021). Free Universities. Putting the Academic Freedom Index into Action. Report, March, Global Public Policy Institute (GPPi). https://gppi.net/media/KinzelbachEtAl_2021_Free_Universities_AFi-2020_upd.pdf
- Lyer, K. R., Saliba, I., & Spannagel, J. (2022). University Autonomy Decline: Causes, Responses, and Implications for Academic Freedom. Taylor & Francis Limited. https://doi.org/10.4324/9781003306481
- Kinzelbach, Katrin. (2020). Researching Academic Freedom: Guidelines and Sample Case Studies. In FAU Studien zu Menschenrechten; 5. FAU University Press. https://doi.org/10.25593/978-3-96147-370-0
- Pelke, L., Spannagel, J., & Kinzelbach, K. (2022). Wissenschaftsfreiheit weltweit und internationale akademische Mobilität in Deutschland (1st ed.). Deutscher Akademischer Austauschdienst (DAAD). https://doi.org/10.46685/DAADStudien.2022.11
- Spannagel, J., & Kinzelbach, K. (2021). Die Vermessung von Wissenschaftsfreiheit. APuZ. Aus Politik und Zeitgeschichte, 46, 34–41. https://www.bpb.de/shop/zeitschriften/apuz/wissenschaftsfreiheit-2021/343232/die-vermessung-von-wissenschaftsfreiheit/