AMI

About

The AMI Project

An independent index measuring the prevalence of academic cheating and the quality of institutional responses across 28 countries.

Founder

FB

Francisco Booth

Independent researcher

Francisco Booth is an independent researcher who created the Academic Misconduct Index in 2026. The AMI is his original research project, built with open data sources and a transparent methodology designed to be independently verifiable.

The index

The AMI is modelled structurally on the Corruption Perceptions Index (CPI) published annually by Transparency International. The first CPI (1995) was built entirely from existing surveys and risk assessments before Transparency International commissioned its own expert perception surveys. The AMI follows the same approach: version 1.x aggregates existing data; version 2.0 will add expert perception surveys once the index has an established audience.

All data, methodology, and source code are released openly under Creative Commons Attribution 4.0. You are free to reuse, republish, or build on this work with attribution.

Why academic misconduct matters

Credential inflation

When degrees can be obtained through fraud, they become less reliable signals of competence. Employers and graduate schools bear the cost of credentials they cannot trust.

Research integrity

Data fabrication and falsification corrupt the scientific record. Retracted papers continue to be cited post-retraction, meaning the harm compounds over time.

Public accountability

No systematic cross-country index of academic misconduct previously existed. The AMI creates a baseline against which progress — or deterioration — can be measured.

Contact and press

For media enquiries, methodology questions, or data corrections, the best approach is to raise an issue on the public GitHub repository, or to reach out directly.

Version history

v1.3

April 2026

Added essay mill brand Trends, FOI-derived AI misconduct rates for 13 countries, ICAI country-level survey data for 20 countries (D4) and 15 countries (D5). 27/28 countries at quality flag A.

v1.2

April 2026

Fixed enforcement-detection correction over-amplification. Added country-differentiated D1 and D2 literature estimates. All 28 countries scoring across 6 dimensions.

v1.1

April 2026

Initial public release. 28 countries, 6 dimensions, literature-derived weighting, Retraction Watch and Google Trends live data.