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# What Happens When You Map 831 Russian Prosecutions to the Sustainable Development Goals
- URL: https://www.traceoriginresearch.com/831-prosecutions-filed-against-education-what-happens-when-you-map-russias-political-charges-to-the-sustainable-development-goals/
- Published: 2026-09-17T20:42:55.000Z
- Updated: 2026-09-20T02:52:40.000Z
- Author: Eric Brattin
- Tags: Russia, Global

Trace Origin LLC · Preliminary Analysis · Data: OVD-Info

7,132 prosecutions · 8 SDG domains · 1 mapping

## Political prosecution targets more than rights. It targets *development.*

When governments report progress on the UN Sustainable Development Goals, political prisoners do not appear in the data. Prosecutions are classified as criminal justice. The people they remove from society (researchers, journalists, activists, religious minorities, organizers) are classified as offenders. The development domains those people serve are never named. This analysis names them.

Russia has politically prosecuted 7,132 people in the OVD-Info dataset. Each prosecution is filed under a specific Criminal Code article. Each article targets a specific category of person. And each category of person corresponds to a specific SDG domain. Art. 280 (extremist speech) silences the academics and journalists who sustain SDG 4 (Quality Education). Art. 275 (treason) criminalizes the international scientific collaboration that sustains SDG 9 (Innovation). Art. 205.5 (terrorism) targets the ethnic and religious minorities whose inclusion defines SDG 10 (Reduced Inequalities). Art. 282.1 (extremist organization) liquidates the NGOs that sustain SDG 17 (Partnerships for the Goals).

We mapped every prosecution in the dataset to the SDG it most directly damages, using a SKOS vocabulary that links each Criminal Code article to its functional target. The result is not a correlation between prosecution and development decline. It is a direct count, validated against the 217,814-triple knowledge graph: 831 prosecutions classified as potentially impeding SDG 4\. 1,950 filed against SDG 10\. 238 filed against SDG 9\. 83.6% of the SDG 4 prosecutions happened after the February 2022 invasion. 4,040 people face charges that damage two or more SDG domains simultaneously. 15 of those people are children.

**The implication for policy:** political prosecution is conventionally placed under SDG 16 (Peace, Justice and Strong Institutions) and treated as a governance problem. This analysis shows it is also an education problem (SDG 4), an innovation problem (SDG 9), an inequality problem (SDG 10), an economic growth problem (SDG 8), and a partnerships problem (SDG 17). Governments that prosecute political dissent are not failing on one SDG. They are failing on six. International development institutions (the World Bank, UNDP, bilateral aid agencies) that treat governance and development as separate policy domains are measuring the damage with the wrong instrument.

5,700

Unique persons whose  
charges impede  
7 SDG domains

83.6%

Of education-domain  
prosecutions occurred  
after Feb 2022

15

Children face charges  
that impede  
education (SDG 4)

the mapping

## Which SDG does each prosecution category *damage?*

CHARGE-TO-SDG MAPPING: 7,132 RUSSIAN PROSECUTIONS ACROSS 8 SDG DOMAINS SDG 16: Institutions 5,376 SDG 17: Partnerships 2,158 Organizational + treason charges SDG 10: Inequality 1,950 Terrorism charges targeting ethnic minorities SDG 4 831 Education: speech crimes chilling academic freedom 83.6% post-invasion SDG 5: Gender · 288 0/288 women in terror training SDG 8: Growth · 270 Protest charges suppressing labor organizing SDG 9: Innovation · 238 Treason charges against scientists 81.6% post-invasion SDG 3: Health 2,174 imprisoned, 78 deceased Bar width proportional to prosecution count. Counts from knowledge graph (217,814 triples). Prosecutions may map to multiple SDGs. Totals above count unique persons per domain. 4,040 people face charges damaging 2+ SDG domains simultaneously. 7 people face 5 domains. 

Fig. 1 Every prosecution in the OVD-Info dataset mapped to the SDG it most directly damages, via the SKOS charge vocabulary. SDG 16 (institutions) absorbs the largest share, but SDGs 4 (education), 9 (innovation), 10 (inequality), and 17 (partnerships) each absorb hundreds of prosecutions. The post-invasion concentration is highest for SDG 4 (83.6%) and SDG 9 (81.6%): the wartime speech and treason articles disproportionately damage education and innovation.

the acceleration

## The invasion changed which SDGs are under *attack.*

PROSECUTIONS PER SDG DOMAIN BY YEAR (RUSSIA, 2015-2026) 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Feb 2022 950 475 0 Institutions Inequality Partnerships Education Innovation Education and Innovation were near zero before invasion 

Fig. 2 Prosecutions per SDG domain by year. SDG 16 (institutions) was the dominant target throughout, but accelerated sharply after the invasion. SDG 4 (education) and SDG 9 (innovation) were near zero before 2022 and spiked after the invasion as speech and treason charges were deployed against academics and scientists. SDG 17 (partnerships) peaked in 2021 (extremist organization designations) and remains elevated. The invasion did not create political prosecution. It redirected it toward education and innovation.

Education and innovation were nearly untouched before the invasion. 83.6% of education-related prosecutions (SDG 4) and 81.6% of innovation-related prosecutions (SDG 9) occurred after February 2022\. The wartime articles (207.3, 280.3, 354.1, 275) are not just human rights violations. They are instruments aimed at the people who educate, research, and innovate, and the development domains those people serve.

the mechanism

## How each prosecution category damages a specific *SDG.*

PROSECUTION CATEGORY TO SDG IMPACT: 8 TRANSMISSION MECHANISMS CHARGE CATEGORY MECHANISM SDG DAMAGED Speech (280, 354.1, 207.3) Chills academic discourse, drives 2,500 researchers into exile SDG 4: Education (831) Treason (275, 276) Criminalizes international scientific collaboration SDG 9: Innovation (238) Terrorism (205, 205.3-5) Targets Crimean Tatars, JW, Hizb ut-Tahrir members SDG 10: Inequality (1,950) Organizational (282.1-2) Liquidates NGOs, designates orgs as extremist (Memorial, FBK) SDG 17: Partnerships (2,158) Protest (212, 318) Suppresses labor organizing, economic grievance expression SDG 8: Growth (270) All charges (imprisonment) Imprisonment deteriorates health; 78 deceased, torture documented SDG 3: Health (78 deceased) Terrorism (205.3, gendered) 0/288 women in terror training; gendered application of harshest charges SDG 5: Gender (0/288) Each arrow represents a documented transmission mechanism from prosecution to development impact. Numbers in parentheses are prosecution counts from OVD-Info mapped through the SKOS charge vocabulary. Brain drain figures: 650,000 emigrated (OutRush/The Bell), 2,500 researchers (Novaya Gazeta/ORCID). 

Fig. 3 The transmission mechanism from prosecution to SDG impact. Each row shows one prosecution category, the mechanism through which it damages development, and the SDG it targets. The mapping is not speculative: each link is supported by documented evidence (brain drain statistics, organizational liquidation records, ethnic targeting patterns, labor suppression). The charge-to-SDG connection passes through the SKOS vocabulary that maps each Criminal Code article to its functional purpose.

what the knowledge graph made easier to find

## Three findings that required the *knowledge graph.*

The charge-to-SDG mapping can be computed in Python. The following three findings require connecting four layers of data simultaneously: the person (age, gender), the prosecution (charge, year), the Criminal Code article, and the SDG domain it damages. Any relational database or data analysis tool could produce the same results with the right joins. The knowledge graph makes these queries composable without schema redesign, reusable across jurisdictions, and extensible as new SDG mappings or country datasets are added. That is a practical advantage for a multi-country research program, not a computational requirement.

### Finding 1: Children prosecuted per SDG domain

CHILDREN PROSECUTED PER SDG DOMAIN (knowledge graph traversal) SDG 16: Institutions 35 SDG 10: Inequality 18 SDG 4: Education 15 SDG 17: 2 · SDG 5: 2 · SDG 8: 1 · SDG 9: 1 15 children prosecuted under charges that damage education (SDG 4). 

Fig. 5 Children (under 18 at prosecution) per SDG domain. 15 children face charges that damage SDG 4 (education): speech crimes that chill the academic environment these children should be entering, applied to people who are themselves still in school. 18 face charges targeting SDG 10 (inequality): terrorism articles disproportionately applied to ethnic minorities. This finding connects person (birth year), prosecution (charge article, year), and SDG mapping. The same result is achievable with joined tables. The knowledge graph makes it reusable: adding a new country requires only new charge-to-SDG mappings, not a new query.

### Finding 2: Compound SDG damage per person

HOW MANY SDG DOMAINS DOES EACH PERSON'S PROSECUTION DAMAGE? (knowledge graph traversal) 1 SDG 1,029 2 SDGs 4,040 70.8% of all mapped persons 3 529 4 SDGs: 95 · 5 SDGs: 7 

Fig. 6 Compound SDG damage per person. 4,040 people (70.8% of all persons with SDG-mapped charges) face prosecutions that damage two SDG domains simultaneously. 529 face three. 95 face four. 7 people face charges that damage five SDG domains at once. A caveat: because individual articles map to multiple SDGs by design (Art. 280 maps to both SDG 16 and SDG 4), some of this multiplicity is built into the ontology rather than discovered in the data. A person charged under Art. 280 automatically appears in two SDG domains. The 70.8% figure reflects both the prosecution pattern and the mapping structure. It would be lower under a one-article-one-SDG rule. We report it with this caveat rather than presenting it as a purely empirical finding.

### Finding 3: Russia applies its harshest charges exclusively to men

288 people have been charged under Art. 205.3 (terror training), the charge that carries the longest sentences in the political prosecution system. All 288 are male. Zero are women. This is not a sampling artifact. It is a pattern: the Russian state applies its most severe political prosecution instrument exclusively to one gender.

We report this as a standalone prosecution finding, not as an SDG indicator. The standard UN SDG 5 framework focuses on empowering women and closing gender gaps. The 0/288 pattern is the opposite: men bear the heaviest prosecution burden. It is a gendered institutional pattern worth documenting, but it does not belong inside the SDG mapping framework. We initially classified it under SDG 5 and have moved it here on review.

Across all SDG domains, women comprise 17.5% of SDG 16 prosecutions, 22.2% of SDG 17, 10.7% of SDG 10, 16.3% of SDG 4, and 0.0% of SDG 5\. The harshest charges (terrorism) are applied almost exclusively to men. The development consequence: the gendered prosecution pattern shapes which SDG domains absorb the most severe sentences.

the argument

## This is not a correlation. It is a *mapping.*

Three kinds of claims exist in this space. This analysis makes the third.

**Correlation** runs a regression: prosecution count goes up, life expectancy goes down, a p-value falls below 0.05\. The problem is that both variables are driven by the same political crisis. The regression finds that bad things happen together. That is not a finding. We ran this analysis (panel fixed-effects, four countries, 639 observations). It produced statistically significant but substantively ambiguous results, because prosecution and SDG decline are both symptoms of the same event.

**Causation** compares an observed trajectory to a counterfactual: what would Russia's SDG indicators have done if it had not escalated prosecution? This requires a synthetic control (Abadie et al., 2010) or a difference-in-differences design with a non-escalating comparator. We attempted this using 12 control countries. It returned no significant results because the post-escalation time series are too short (2-3 years) and the confounders (sanctions, war, mobilization) are too large. This analysis will gain power as more data accumulates. It is not ready.

**Mapping** does neither. It classifies each individual prosecution by the SDG domain it impedes, based on the legal function of the charge article. Art. 354.1 (rehabilitation of Nazism) is a speech crime applied to academics and students. Speech crimes against academics impede education. Education is SDG 4\. Therefore this prosecution maps to SDG 4\. The number 831 is not a regression coefficient. It is a count of prosecutions whose charge article, by its legal function, impedes SDG 4\. No p-value is needed because no statistical inference is being made. The claim is taxonomic, not causal.

The strength of mapping is that no confounder can invalidate it. Sanctions did not cause 831 prosecutions to be filed under speech articles against people in educational contexts. The state did that. The mapping counts what the state did, classified by which development domain it targeted.

The weakness of mapping (identified through red-teaming) is that the taxonomy is analyst judgment. Art. 275 (treason) maps to SDG 9 (innovation) only if the defendant is a scientist. If the defendant is a military officer, the mapping is wrong. The OVD-Info dataset does not include defendant occupation, so the knowledge graph cannot disambiguate at the person level. The SDG 9 count (238) should be read as an upper bound. A stronger version of this analysis would filter treason cases to those where journalism or court records identify the defendant's profession.

For the proposed joint SDG reportThis mapping framework can be applied to every country in the proposed collaboration (Azerbaijan, Georgia, Egypt, Nicaragua, Venezuela, plus Russia, Belarus, Cuba). Each country's prosecution dataset would be mapped through a country-specific SKOS vocabulary to the same SDG domain structure. The output is comparable across countries: how many prosecutions does each system file against each SDG? The pipeline is operational for five countries. Extending it to five more requires the prosecution data, country-specific charge-to-SDG mappings, and independent validation of each mapping. Because the mappings are analyst judgments, different analysts may produce different SDG allocations for the same charge in different jurisdictions. The joint report should establish a shared mapping protocol (inter-coder reliability testing, minimum two analysts per country) before presenting cross-country comparisons. 

methodological note

## How to read the *numbers.*

**Double-counting rule:** A single prosecution can map to multiple SDGs. Art. 280 (extremist speech) maps to both SDG 16 (institutions) and SDG 4 (education). The 5,376 SDG 16 prosecutions and the 831 SDG 4 prosecutions overlap. The total number of unique persons with SDG-mapped charges is 5,700\. Because individual articles map to multiple SDGs (Art. 280 maps to both SDG 16 and SDG 4), the total count of person-SDG pairings is higher than the person count. Both numbers are correct. The first counts people. The second counts the development domains each person's prosecution damages. This report uses the SDG-event count (\~11,100) because the argument is about breadth of damage, not headcount.

**What the mapping measures and what it does not:** The charge-to-SDG mapping is an analyst judgment, not an automated classification. Each link is defensible (Art. 275 treason against scientists \\uc0\\u8594 SDG 9 innovation is a direct causal mechanism), but alternative mappings are possible. The mapping does not measure the magnitude of damage per prosecution. A 20-year terrorism sentence removes more human capital than a 3-year speech charge. A future iteration should weight by sentence length.

**SDG 13 (Climate Action):** The Russian dataset contains few prosecutions of environmental activists specifically. But for the proposed cross-country expansion (Azerbaijan, Georgia, Egypt, Nicaragua, Venezuela), prosecution of environmental defenders maps directly to SDG 13\. The framework includes SDG 13 as a placeholder for countries where that pattern is documented. This brings the total framework to 9 SDG domains, of which 8 are populated from the Russian data.

Preliminary analysis. The pipeline is ready.

Prosecution data: OVD-Info (7,132 Russian cases). SKOS charge vocabulary: 26 Criminal Code articles mapped to 7 SDG domains. All counts validated against the 217,814-triple knowledge graph.  
Brain drain data: OutRush/Stanford (650,000 emigrated), Novaya Gazeta/ORCID (2,500 researchers), Nature Index (-17%).  
Method: SKOS charge-to-SDG mapping (analyst judgment). Each prosecution classified by the SDG domain it impedes.  
Proposed: extend to Azerbaijan, Georgia, Egypt, Nicaragua, Venezuela via joint OVD-Info report.  
  
© 2026 Trace Origin LLC. Prosecution data: OVD-Info (used with permission). SDG mapping and analysis: Trace Origin.