Academic Freedom Index AFI

Research

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.

Reports

The image shows the Academic Freedom Index Update 2024 cover. It shows students and reseachers looking at a world map.
Cover of the Academic Freedom Index Report

Based on assessment of the de facto protection of academic freedom as of December 2023, the Academic Freedom Index Update 2024 provides an overview of the state of academic freedom in 179 countries and territories. In line with previous AFI reports, this year’s data demonstrates that academic freedom is under threat globally. Using the concept of growth and decline episodes at country level, this year’s update shows that 23 countries are in episodes of decline in academic freedom, but academic freedom is increasing in only ten countries. 3.6 billion people now live in countries where academic freedom is completely restricted. Taking a longer time period into account by comparing 2023 data with that of fifty years ago, we note more optimistically that academic freedom expanded in 56 countries.

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.

Method

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 2,329 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 2,329 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. (2023). The Academic Freedom Index and its indicators: Introduction to new global time-series V-Dem data. Quality & Quantity 57: 3969–89>. https://doi.org/10.1007/s11135-022-01544-0

Expert-Coded Data

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.

Publications

Here you can find peer-reviewed publications and other material from the AFI Team about the Academic Freedom Index.

Academic Freedom Index Update Reports