2c:null 2d:["$","title",null,{"children":"Data on foreign agents and undesirable organisations | Daniil Beilinson | Observable"}] 32:T4c8,Plot.plot({ x: {label: null, axis: null}, color: {scheme: "Paired"}, width: 800, caption: 'Distribution of foreign agents by gender', marks: [ Plot.barX( entitiesData.filter(i => i.isForeignAgent && i.type === 'Person'), Plot.stackX( Plot.binX( {x: "count"}, { fill: "gender", fillOpacity: 0.3, insetRight: 5, marginBottom: 30, tip: true } ) ) ), Plot.textX( entitiesData.filter(i => i.isForeignAgent && i.type === 'Person'), Plot.stackX( Plot.binX( {x: "count", text: d => d[0].gender}, { z: "gender", lineWidth: 10, inset: 5, } ) ) ), Plot.textX( entitiesData.filter(i => i.isForeignAgent && i.type === 'Person'), Plot.stackX( Plot.binX( {x: "count"}, { z: "gender", text: (d,i,a) => `${d.length.toLocaleString()} (${Math.round((100 * d.length) / a.reduce((a,i) => a + i.length, 0))}%)`, inset: 5, lineAnchor: "top", dy: 20 } ) ) ) ] })33:T547,Plot.plot({ x: {label: null, axis: null}, color: {scheme: "Pastel1"}, width: 800, caption: 'Distribution of foreign agents by age group', marks: [ Plot.barX( entitiesData.filter(i => i.isForeignAgent && i.type === 'Person'), Plot.stackX( Plot.binX( {x: "count", sort: "count"}, { fill: "ageGroup", fillOpacity: 0.3, insetRight: 5, marginBottom: 30, tip: true } ) ) ), Plot.textX( entitiesData.filter(i => i.isForeignAgent && i.type === 'Person'), Plot.stackX( Plot.binX( {x: "count", text: d => d.length > 40 ? d[0].ageGroup : "", sort: "count"}, { z: "ageGroup", lineWidth: 10, inset: 5, } ) ) ), Plot.textX( entitiesData.filter(i => i.isForeignAgent && i.type === 'Person'), Plot.stackX( Plot.binX( {x: "count", sort: "count"}, { z: "ageGroup", text: (d,i,a) => d.length > 40 ? `${d.length.toLocaleString()} (${Math.round((100 * d.length) / a.reduce((a,i) => a + i.length, 0))}%)` : `${d.length.toLocaleString()}`, inset: 5, lineAnchor: "top", dy: 20 } ) ) ) ] })34:T44f,{ const getStatsForRegion = iso => faOptions === 'any' ? entitiesData.filter(i => i.isForeignAgent && i.regionISO === iso).length : entitiesData.filter(i => i.isForeignAgent && i.type === faOptions && i.regionISO === iso).length return Plot.plot({ width: 975, height: 500, caption: `Number of foreign agents${faOptions !== 'any' ? ' (' + faOptions + ' only)' : ''} by region (including annexed territory of Crimea)`, color: { scheme: "Oranges", type: "symlog" }, projection: { type: "mercator", rotate: [-70, -30, -15], domain: { type: "Polygon", coordinates: [ [ [120,40],[45,82],[50,82],[120,40] ] ] } }, marks: [ Plot.geo(russiaAndAnnexedRegions, {strokeOpacity: 0.2}), Plot.geo(russiaAndAnnexedRegions, {fill: d => getStatsForRegion(d.properties.iso) }), Plot.tip(russiaAndAnnexedRegions.features, Plot.pointer(Plot.centroid({ title: d => `${d.properties.name_en}\nTotal: ${getStatsForRegion(d.properties.iso)}` }))) ] }) }35:T557, ${Object.values(entitiesData.filter(i => i.isForeignAgent).reduce((acc, item) => { if (!item.regionISO) item.region = 'Unknown (no data)' if (!acc[item.regionISO]) acc[item.regionISO] = { title: item.region, all: 0, Organisation: 0, Individual: 0 } acc[item.regionISO].all++ if (item.type === 'Person') acc[item.regionISO].Individual++ if (item.type === 'Organisation') acc[item.regionISO].Organisation++ return acc }, {})).sort((a,b) => b[faOptions] - a[faOptions]).filter(r => r.all > 10).map(region => htl.html``)}

Region	Total	Organisations	Individuals
${region.title}	${region.all} (${(region.all/entitiesData.filter(i => i.isForeignAgent).length).toLocaleString(undefined, { style: 'percent' })})	${region.Organisation} (${(region.Organisation/entitiesData.filter(i => i.isForeignAgent && i.type === 'Organisation').length).toLocaleString(undefined, { style: 'percent' })})	${region.Individual} (${(region.Individual/entitiesData.filter(i => i.isForeignAgent && i.type === 'Person').length).toLocaleString(undefined, { style: 'percent' })})

36:Ta8f,Plot.plot({ marginLeft: 150, x: {label: "Number of foreign agents"}, y: {label: null}, color: { scheme: "Paired", legend: true }, marks: [ Plot.barX(entitiesData.filter(i => i.isForeignAgent && i.type === 'Organisation'), Plot.binX( { x: "count" }, { y: d => "1. Organisations", fill: "category" } )), Plot.text(entitiesData.filter(i => i.isForeignAgent && i.type === 'Organisation'), Plot.binX( { x: "count", text: "count" }, { y: d => "1. Organisations", textAnchor: "begin", dx: 10, fill: "black" } )), Plot.barX(entitiesData.filter(i => i.isForeignAgent && i.type === 'Organisation' && i.isClosed === 'true'), Plot.binX( { x: "count" }, { y: d => "2. Closed organisations", fill: "category" } )), Plot.text(entitiesData.filter(i => i.isForeignAgent && i.type === 'Organisation' && i.isClosed === 'true'), Plot.binX( { x: "count", text: "count" }, { y: d => "2. Closed organisations", textAnchor: "begin", dx: 10, fill: "black" } )), Plot.barX(entitiesData.filter(i => i.isForeignAgent && i.isExcluded === 'true'), Plot.binX( { x: "count" }, { y: d => "3. Excluded from registry", fill: "category" } )), Plot.text(entitiesData.filter(i => i.isForeignAgent && i.isExcluded === 'true'), Plot.binX( { x: "count", text: "count" }, { y: d => "3. Excluded from registry", textAnchor: "begin", dx: 10, fill: "black" } )), Plot.barX(entitiesData.filter(i => i.isForeignAgent && i.type === 'Person'), Plot.binX( { x: "count" }, { y: d => "4. Individuals", fill: "category" } )), Plot.text(entitiesData.filter(i => i.isForeignAgent && i.type === 'Person'), Plot.binX( { x: "count", text: "count" }, { y: d => "4. Individuals", textAnchor: "begin", dx: 10, fill: "black" } )), Plot.barX(entitiesData.filter(i => i.isForeignAgent && i.isAntiwar === true), Plot.binX( { x: "count" }, { y: d => "5. Public antiwar position", fill: "category" } )), Plot.text(entitiesData.filter(i => i.isForeignAgent && i.isAntiwar === true), Plot.binX( { x: "count", text: "count" }, { y: d => "5. Public antiwar position", textAnchor: "begin", dx: 10, fill: "black" } )), Plot.barX(entitiesData.filter(i => i.isForeignAgent && i.underPersecution === true), Plot.binX( { x: "count" }, { y: d => "6. Has criminal cases", fill: "category" } )), Plot.text(entitiesData.filter(i => i.isForeignAgent && i.underPersecution === true), Plot.binX( { x: "count", text: "count" }, { y: d => "6. Has criminal cases", textAnchor: "begin", dx: 10, fill: "black" } )), Plot.ruleX([0]) ] })37:T4aa,Plot.plot({ x: {label: null, axis: null}, color: {scheme: "Paired"}, width: 800, caption: 'Distribution of administrative cases under foreign agents legislation by gender', marks: [ Plot.barX( admCasesData.filter(i => i.isForeignAgent), Plot.stackX( Plot.binX( {x: "count"}, { fill: "gender", fillOpacity: 0.3, insetRight: 5, marginBottom: 30, tip: true } ) ) ), Plot.textX( admCasesData.filter(i => i.isForeignAgent), Plot.stackX( Plot.binX( {x: "count", text: d => d[0].gender}, { z: "gender", lineWidth: 10, inset: 5, } ) ) ), Plot.textX( admCasesData.filter(i => i.isForeignAgent), Plot.stackX( Plot.binX( {x: "count"}, { z: "gender", text: (d,i,a) => `${d.length.toLocaleString()} (${Math.round((100 * d.length) / a.reduce((a,i) => a + i.length, 0))}%)`, inset: 5, lineAnchor: "top", dy: 20 } ) ) ) ] })38:T55f, ${Object.values(admCasesData.filter(i => i.isForeignAgent).reduce((acc, item) => { if (!item.regionISO) item.region = 'Unknown (no data)' if (!acc[item.regionISO]) acc[item.regionISO] = { title: item.region, total: 0, penalty: 0, other: 0 } acc[item.regionISO].total++ if (item.decision === 'Administrative penalty imposed') acc[item.regionISO].penalty++ if (item.decision !== 'Administrative penalty imposed' && item.decision !== 'Unknown or in progress') acc[item.regionISO].other++ return acc }, {})).sort((a,b) => b.total - a.total).filter(r => r.total > 10).map(region => htl.html``)}

Region	Total cases	Penalty	Other decisions
${region.title}	${region.total} (${(region.total/admCasesData.filter(i => i.isForeignAgent).length).toLocaleString(undefined, { style: 'percent' })})	${region.penalty} (${(region.penalty/admCasesData.filter(i => i.isForeignAgent).length).toLocaleString(undefined, { style: 'percent' })})	${region.other} (${(region.other/admCasesData.filter(i => i.isForeignAgent).length).toLocaleString(undefined, { style: 'percent' })})

39:T4b2,Plot.plot({ x: {label: null, axis: null}, color: {scheme: "Paired"}, width: 800, caption: 'Distribution of administrative cases under undesirable organisations legislation by gender', marks: [ Plot.barX( admCasesData.filter(i => i.isUndesirable), Plot.stackX( Plot.binX( {x: "count"}, { fill: "gender", fillOpacity: 0.3, insetRight: 5, marginBottom: 30, tip: true } ) ) ), Plot.textX( admCasesData.filter(i => i.isUndesirable), Plot.stackX( Plot.binX( {x: "count", text: d => d[0].gender}, { z: "gender", lineWidth: 10, inset: 5, } ) ) ), Plot.textX( admCasesData.filter(i => i.isUndesirable), Plot.stackX( Plot.binX( {x: "count"}, { z: "gender", text: (d,i,a) => `${d.length.toLocaleString()} (${Math.round((100 * d.length) / a.reduce((a,i) => a + i.length, 0))}%)`, inset: 5, lineAnchor: "top", dy: 20 } ) ) ) ] })3a:T55e, ${Object.values(admCasesData.filter(i => i.isUndesirable).reduce((acc, item) => { if (!item.regionISO) item.region = 'Unknown (no data)' if (!acc[item.regionISO]) acc[item.regionISO] = { title: item.region, total: 0, penalty: 0, other: 0 } acc[item.regionISO].total++ if (item.decision === 'Administrative penalty imposed') acc[item.regionISO].penalty++ if (item.decision !== 'Administrative penalty imposed' && item.decision !== 'Unknown or in progress') acc[item.regionISO].other++ return acc }, {})).sort((a,b) => b.total - a.total).filter(r => r.total > 10).map(region => htl.html``)}

Region	Total cases	Penalty	Other decisions
${region.title}	${region.total} (${(region.total/admCasesData.filter(i => i.isForeignAgent).length).toLocaleString(undefined, { style: 'percent' })})	${region.penalty} (${(region.penalty/admCasesData.filter(i => i.isForeignAgent).length).toLocaleString(undefined, { style: 'percent' })})	${region.other} (${(region.other/admCasesData.filter(i => i.isForeignAgent).length).toLocaleString(undefined, { style: 'percent' })})

3b:T585,entitiesData = entitiesRawData.map(item => ({ name: item.Name, included: new Date(item['Date of inclusion']), status: item['Status'].replaceAll("\"",""), isUndesirable: item['Status'].replaceAll("\"","") === "Undesirable organization", isForeignAgent: item['Status'].replaceAll("\"","") !== "Undesirable organization", type: item['Natural person or legal entity'] === 'Natural person' ? 'Person' : 'Organisation', area: item['Field of activity'], gender: item['Natural person or legal entity'] === 'Natural person' ? item['Пол'] === 'М' ? 'male' : 'female' : '', category: item['Natural person or legal entity'] === 'Natural person' ? item['Пол'] === 'М' ? 'male person' : 'female person' : 'organisation', age: item['Возраст на момент внесения'], ageGroup: item['Age group at the moment of inclusion'], isAntiwar: item["\"Антивоенное\""], isClosed: item['Closed'], isExcluded: item['Excluded from register'], excluded: new Date(item['МЮ: Дата принятия решения об исключении']), underPersecution: item['Наличие уголовного преследования'], persecutionStarted: item['Дата начала преследования'], articles: item['Article of Criminal Code'], region: item['Region (by tax number)'], regionISO: item['Region ISO (by tax number)'] }))3c:[{"id":"0f0f63f12052756f27afaafc4825cf30353fd3af8ec81d24d83e59dad44bca268735dbd7fd534aa39b16a86882f559005d825d98c6d02b0d9f2ffb9ef7681c48","href":"https://static.observableusercontent.com/files/0f0f63f12052756f27afaafc4825cf30353fd3af8ec81d24d83e59dad44bca268735dbd7fd534aa39b16a86882f559005d825d98c6d02b0d9f2ffb9ef7681c48","name":"russia-and-annexed-regions-compressed.json","type":"application/json","lastModified":1705531898431.686,"size":80740}] 30:{"id":"41d1d28c0711bb07","slug":"data-on-foreign-agents-and-undesirable-organisations","title":"Data on foreign agents and undesirable organisations","thumbnail":"99cf310fce0db7eee18f8db626214b7a4bc599403a7dbb3a8da34490e8e0ad91","access_level":"public","create_time":"$D2024-01-16T20:24:45.164Z","update_time":"$D2025-10-15T09:42:14.704Z","view_time":null,"first_public_time":"$D2024-01-16T20:24:45.164Z","fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"9b6646ec24dff9ba","login":"d-beilinson","name":"Daniil Beilinson","avatar_url":"https://avatars-next.observableusercontent.com/2d93226084d84c384a572996c4ef629251636290e2358a9491c05b7a329cc05b","tier":"starter_2024"},"version":881,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"ebe552f4a6dc3f7f","login":"daniil-beilinson","name":"Daniil Beilinson","avatar_url":"https://avatars-next.observableusercontent.com/b2df9a708eacdc151433d21ffde2c2a5a7e14023c8175bb08d2f4f6aceb3b7ce","tier":null}],"members":[{"type":"individual","id":"ebe552f4a6dc3f7f","login":"daniil-beilinson","name":"Daniil Beilinson","avatar_url":"https://avatars-next.observableusercontent.com/b2df9a708eacdc151433d21ffde2c2a5a7e14023c8175bb08d2f4f6aceb3b7ce","tier":null,"role":"editor"},{"type":"team","id":"9b6646ec24dff9ba","login":"d-beilinson","name":"Daniil Beilinson","avatar_url":"https://avatars-next.observableusercontent.com/2d93226084d84c384a572996c4ef629251636290e2358a9491c05b7a329cc05b","tier":"starter_2024","role":"editor"}],"comments":[],"custom_thumbnail":true,"trashed":false,"subscribed":null,"forks":0,"collection":null,"type":"notebook","body":{"title":"Data on foreign agents and undesirable organisations","cells":[{"id":0,"value":"# Data on foreign agents and undesirable organisations","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":684,"value":"note(md`This computational notebook prepared as the additional material for the joint seminar [\"Political Repression in Russia, 2012-2023](https://cercec.ehess.fr/evenement/joint-seminar-political-repression-russia-2012-2023). The notebook explores two datasets available at [the end of the document](#cell-652)).`)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":670,"value":"toc()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":38,"value":"# Foreign agents","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":714,"value":"According to the published dataset, there are ${entitiesData.filter(i => i.isForeignAgent).length} foreign agents. ${entitiesData.filter(i => i.isForeignAgent && i.type === 'Person').length} of them are individuals and ${entitiesData.filter(i => i.isForeignAgent && i.type === 'Organisation').length} are organisations. \n\nThe graph below is showing how the registries of foreign agents were expanding throughout the years.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":40,"value":"Plot.plot({\n color: { scheme: \"Paired\", legend: true },\n caption: 'Expansion of the register of foreign agents by individuals and legal entities per year',\n y: {\n grid: true,\n label: \"Total\"\n },\n x: {\n label: \"Date\"\n },\n marks: [\n Plot.rectY(entitiesData.filter(i => i.isForeignAgent), Plot.binX({y: \"count\"}, {x: \"included\", interval: 'year', fill: \"type\", tip: true})),\n Plot.text(entitiesData.filter(i => i.isForeignAgent), Plot.binX(\n { y: \"count\", text: d => d.length },\n { x: \"included\", interval: 'year', textAnchor: \"middle\", dy: -10, fill: \"black\" }\n )),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":721,"value":"Certain fields of activities became specific target of the law application. The graph below shows which areas are affected the most.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":65,"value":"Plot.plot({\n caption: 'Distribution of foreign agents by field of activity and gender',\n marginLeft: 250,\n marginRight: 60,\n width: 800,\n y: { label: \"Field of activity\", },\n x: { label: \"# of foreign agents\" },\n color: { scheme: \"Paired\", legend: true },\n marks: [\n Plot.barX(entitiesData.filter(i => i.isForeignAgent), Plot.groupY(\n { x: \"count\" },\n { fill: \"category\", y: \"area\", tip: true, sort: { y: \"x\", reverse: true } }\n )),\n Plot.axisY({textAnchor: \"end\", lineWidth: 20, fill: \"black\", dx: -5}),\n Plot.text(entitiesData.filter(i => i.isForeignAgent), Plot.groupY(\n { x: \"count\", text: d => d.length },\n {\n y: \"area\",\n textAnchor: \"begin\",\n dx: 10,\n fill: \"black\"\n }\n ))\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":723,"value":"These graphs providing the information about foreign agents individuals disaggregated by gender and age group.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":107,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":218,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":726,"value":"The information published by the Ministry of Justice includes tax numbers of organisation and individuals. These numbers include in themself the information about the region. This way, we can analyse which regions were mostly affected by the application of the law. \n\n In the table below the map, you may find the information on the 10 most active regions.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":328,"value":"viewof faOptions = Inputs.radio(new Map([[\"Any\", \"any\"], [\"Organisations\", \"Organisation\"], [\"Individuals\", \"Person\"]]), {label: \"Type of foreign agents\", value: \"any\"})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":310,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":334,"value":"$35","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":736,"value":"The active filling of the registers with representatives of certain professions suggests that this phenomenon has the nature of political campaigns. The graph below shows how these campaigns may have developed.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":366,"value":"Plot.plot({\n marginLeft: 250,\n marginRight: 60,\n width: 800,\n y: { label: \"Field of activity\" },\n x: { label: \"Year\" },\n color: {scheme: \"YlOrRd\", legend: true, label: 'Number of foreign agents', type: 'symlog'},\n marks: [\n Plot.rect(entitiesData.filter(i => i.isForeignAgent),\n Plot.binX(\n {fill: \"count\"},\n {x: \"included\", interval: \"year\", y: \"area\", inset: 0.5, tip: true, sort: { y: \"x\", reverse: true }}\n )\n ),\n Plot.axisY({textAnchor: \"end\", lineWidth: 20, fill: \"black\", dx: -5}),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":743,"value":"$${entitiesData.filter(i => i.isForeignAgent && i.isExcluded === 'true').length} foreign agents were excluded from registries. However in many cases it happened after the dissolution of organisation. As of today ${entitiesData.filter(i => i.isForeignAgent && i.type === 'Organisation' && i.isClosed === 'true').length} organisations from registry are not existing. \n\nAt least ${entitiesData.filter(i => i.isForeignAgent && i.isAntiwar === true).length} foreign agents has publicly communicated their antiwar position. This leads to the assumption that this was the reason for some of them to be included in the register. The number of foreign agents with various criminal cases open against them confirms this hypothesis. Today there are at least ${entitiesData.filter(i => i.isForeignAgent && i.underPersecution === true).length} of them.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":446,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":505,"value":"# Undesirable organisations","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":757,"value":"According to the published dataset, there are ${entitiesData.filter(i => i.isUndesirable).length} undesirable organisations. The graph below is showing how the corresponding registry was expanding throughout the years.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":507,"value":"Plot.plot({\n color: { scheme: \"Paired\" },\n y: {\n grid: true,\n label: \"Total\"\n },\n x: {\n label: \"Date\"\n },\n marks: [\n Plot.rectY(entitiesData.filter(i => i.isUndesirable), Plot.binX({y: \"count\"}, {x: \"included\", interval: 'year', fill: \"type\", tip: true})),\n Plot.text(entitiesData.filter(i => i.isUndesirable), Plot.binX(\n { y: \"count\", text: d => d.length },\n { x: \"included\", interval: 'year', textAnchor: \"middle\", dy: -10, fill: \"black\" }\n )),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":763,"value":"As in case with foreign agents, certain fields of activities became specific target of the law application. The graph below shows which areas are affected the most.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":514,"value":"Plot.plot({\n caption: 'Distribution of undesirable organisations by field of activity',\n marginLeft: 250,\n marginRight: 60,\n width: 800,\n y: { label: \"Field of activity\", },\n x: { label: \"# of undesirable organisations\" },\n color: { scheme: \"Paired\" },\n marks: [\n Plot.barX(entitiesData.filter(i => i.isUndesirable), Plot.groupY(\n { x: \"count\" },\n { fill: \"category\", y: \"area\", tip: true, sort: { y: \"x\", reverse: true } }\n )),\n Plot.axisY({textAnchor: \"end\", lineWidth: 20, fill: \"black\", dx: -5}),\n Plot.text(entitiesData.filter(i => i.isUndesirable), Plot.groupY(\n { x: \"count\", text: d => d.length },\n {\n y: \"area\",\n textAnchor: \"begin\",\n dx: 10,\n fill: \"black\"\n }\n ))\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":768,"value":"This graph shows the same data disaggregated by years. Again it emphasizes how the state suddenly used this legislation against specifics activities.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":518,"value":"Plot.plot({\n marginLeft: 250,\n marginRight: 60,\n width: 800,\n y: { label: \"Field of activity\" },\n x: { label: \"Year\" },\n color: {scheme: \"YlOrRd\", legend: true, label: 'Number of undesirable organisations', type: 'symlog'},\n marks: [\n Plot.rect(entitiesData.filter(i => i.isUndesirable),\n Plot.binX(\n {fill: \"count\"},\n {x: \"included\", interval: \"year\", y: \"area\", inset: 0.5, tip: true, sort: { y: \"x\", reverse: true }}\n )\n ),\n Plot.axisY({textAnchor: \"end\", lineWidth: 20, fill: \"black\", dx: -5}),\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":521,"value":"# Administrative cases","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":533,"value":"## Foreign agents legislation (2022-2023)","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":770,"value":"This section explores the dataset of administrative cases profiles for 2022 and 2023 related to the foreign agents legislation. These are the articles 19.34.1 part 1, 19.34.1 part 2, 19.34.1 part 3, 19.34 part 1, 19.34 part 3, 19.7.5-3 part 2, 19.34 part 2, 19.7.5-4 part 2, 19.34 part 4, 19.34 part 5, 19.34 part 8 of the Administrative Code. The data was parsed from the websites of national courts. \n\nThe graph below shows the information on ${admCasesData.filter(i => i.isForeignAgent).length} cases aggregated by the quarter. Note that certain legal entities and their representatives have many cases opened against them.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":537,"value":"Plot.plot({\n caption: 'Number of registered administrative cases under foreign agents legislation',\n color: { scheme: \"Paired\", legend: true },\n y: {\n grid: true,\n label: \"Registered cases\"\n },\n x: {\n label: \"Date\"\n },\n marks: [\n Plot.rectY(admCasesData.filter(i => i.isForeignAgent), Plot.binX({y: \"count\"}, {x: \"registered\", interval: 'quarter', fill: \"gender\", tip: true})),\n Plot.text(admCasesData.filter(i => i.isForeignAgent), Plot.binX(\n { y: \"count\", text: d => d.length },\n { x: \"registered\", interval: 'quarter', textAnchor: \"middle\", dy: -10, fill: \"black\" }\n )),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":776,"value":"In ${admCasesData.filter(i => i.isForeignAgent && i.gender === 'unknown or n/a').length} cases we don't know the gender of the persecuted person or it was an organisation.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":548,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":781,"value":"In ${admCasesData.filter(i => i.isForeignAgent && i.decision === 'Administrative penalty imposed').length} cases, we know that the courts imposed penalty. However, there are the cases when the judges taking the other decisions. The graph below exploring these numbers.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":555,"value":"Plot.plot({\n caption: 'Distribution of administrative cases under foreign agents legislation by decision',\n marginLeft: 250,\n marginRight: 60,\n width: 800,\n y: { label: \"Decision type\" },\n x: { label: \"# of administrative cases\" },\n color: { scheme: \"Paired\", legend: true },\n marks: [\n Plot.barX(admCasesData.filter(i => i.isForeignAgent), Plot.groupY(\n { x: \"count\" },\n { fill: \"gender\", y: \"decision\", tip: true, sort: { y: \"x\", reverse: true } }\n )),\n Plot.axisY({textAnchor: \"end\", lineWidth: 20, fill: \"black\", dx: -5}),\n Plot.text(admCasesData.filter(i => i.isForeignAgent), Plot.groupY(\n { x: \"count\", text: d => d.length },\n {\n y: \"decision\",\n textAnchor: \"begin\",\n dx: 10,\n fill: \"black\"\n }\n ))\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":786,"value":"Since the data was parsed from the websites of regional courts, we can easily disaggregate this data by the region and understand in which regions this legislation is most actively used.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":565,"value":"{\n const getStatsForRegion = iso => admCasesData.filter(i => i.isForeignAgent && i.regionISO === iso).length\n return Plot.plot({ \n width: 975,\n height: 500,\n caption: 'Distribution of administrative cases under foreign agents legislation by region (including annexed territory of Crimea)',\n color: {\n scheme: \"Oranges\",\n type: \"symlog\"\n },\n projection: {\n type: \"mercator\",\n rotate: [-70, -30, -15],\n domain: {\n type: \"Polygon\",\n coordinates: [\n [\n [120,40],[45,82],[50,82],[120,40]\n ]\n ]\n }\n }, \n marks: [\n Plot.geo(russiaAndAnnexedRegions, {strokeOpacity: 0.2}),\n Plot.geo(russiaAndAnnexedRegions, {fill: d => getStatsForRegion(d.properties.iso) }),\n Plot.tip(russiaAndAnnexedRegions.features, Plot.pointer(Plot.centroid({\n title: d => `${d.properties.name_en}\\nTotal: ${getStatsForRegion(d.properties.iso)}`\n })))\n ]\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":569,"value":"$38","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":582,"value":"## Undesirable organisations legislation","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":791,"value":"This section explores the dataset of administrative cases profiles from 2018 until the end of 2023 related to the undesirable organisations legislation, it shows the data regarding application of article `20.33` of the Administrative Code. The data was parsed from the websites of national courts. \n\nThe graph below shows the information on ${admCasesData.filter(i => i.isUndesirable).length} cases aggregated by the year.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":588,"value":"Plot.plot({\n caption: 'Number of registered administrative cases under undesirable organisation legislation',\n color: { scheme: \"Paired\", legend: true },\n y: {\n grid: true,\n label: \"Registered cases\"\n },\n x: {\n label: \"Date\"\n },\n marks: [\n Plot.rectY(admCasesData.filter(i => i.isUndesirable), Plot.binX({y: \"count\"}, {x: \"registered\", interval: 'year', fill: \"gender\", tip: true})),\n Plot.text(admCasesData.filter(i => i.isUndesirable), Plot.binX(\n { y: \"count\", text: d => d.length },\n { x: \"registered\", interval: 'year', textAnchor: \"middle\", dy: -10, fill: \"black\" }\n )),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":797,"value":"In ${admCasesData.filter(i => i.isUndesirable && i.gender === 'unknown or n/a').length} cases we don't know the gender of the persecuted person or it was an organisation.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":592,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":803,"value":"In ${admCasesData.filter(i => i.isForeignAgent && i.decision === 'Unknown or in progress').length} we don't have the data about hte decision. In ${admCasesData.filter(i => i.isForeignAgent && i.decision === 'Administrative penalty imposed').length} from the rest of the cases, we know that the courts imposed penalty. The graph below examines the number of these and other decisions.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":596,"value":"Plot.plot({\n caption: 'Distribution of administrative cases under undesirable organisation legislation by decision',\n marginLeft: 250,\n marginRight: 60,\n width: 800,\n y: { label: \"Decision type\" },\n x: { label: \"# of administrative cases\" },\n color: { scheme: \"Paired\", legend: true },\n marks: [\n Plot.barX(admCasesData.filter(i => i.isUndesirable), Plot.groupY(\n { x: \"count\" },\n { fill: \"gender\", y: \"decision\", tip: true, sort: { y: \"x\", reverse: true } }\n )),\n Plot.axisY({textAnchor: \"end\", lineWidth: 20, fill: \"black\", dx: -5}),\n Plot.text(admCasesData.filter(i => i.isUndesirable), Plot.groupY(\n { x: \"count\", text: d => d.length },\n {\n y: \"decision\",\n textAnchor: \"begin\",\n dx: 10,\n fill: \"black\"\n }\n ))\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":809,"value":"Since this data was also parsed from the websites of regional courts, we can easily disaggregate it by the region and understand in which regions this legislation is most actively used.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":600,"value":"{\n const getStatsForRegion = iso => admCasesData.filter(i => i.isUndesirable && i.regionISO === iso).length\n return Plot.plot({ \n width: 975,\n height: 500,\n caption: 'Distribution of administrative cases under undesirable organisations legislation by region (including annexed territory of Crimea)',\n color: {\n scheme: \"Oranges\",\n type: \"symlog\"\n },\n projection: {\n type: \"mercator\",\n rotate: [-70, -30, -15],\n domain: {\n type: \"Polygon\",\n coordinates: [\n [\n [120,40],[45,82],[50,82],[120,40]\n ]\n ]\n }\n }, \n marks: [\n Plot.geo(russiaAndAnnexedRegions, {strokeOpacity: 0.2}),\n Plot.geo(russiaAndAnnexedRegions, {fill: d => getStatsForRegion(d.properties.iso) }),\n Plot.tip(russiaAndAnnexedRegions.features, Plot.pointer(Plot.centroid({\n title: d => `${d.properties.name_en}\\nTotal: ${getStatsForRegion(d.properties.iso)}`\n })))\n ]\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":610,"value":"$3a","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":524,"value":"# Criminal cases","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":616,"value":"## In relation to foreign agents legislation","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":814,"value":"According to OVD-Info there are at least ${criminalCasesDataFA.data.length} criminal cases with the application of the article 330.1 of the Criminal Code for the breach of the foreign agents legislation. Below is the information about these cases. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":843,"value":"Plot.plot({\n color: { scheme: \"Paired\" },\n caption: `Number of criminal cases per year for evading foreign agent obligations (article 330.1). ${criminalCasesDataFA.data.filter(i => !i.persecution_started_year).length} cases are not shown in the graph because the year when the prosecution began is unknown.`,\n y: {\n grid: true,\n label: \"Number of cases\"\n },\n x: {\n label: \"Year\"\n },\n marks: [\n Plot.rectY(criminalCasesDataFA.data, Plot.binX({y: \"count\"}, {x: \"persecution_started\", interval: 'year', fill: \"type\", tip: true})),\n Plot.text(criminalCasesDataFA.data, Plot.binX(\n { y: \"count\", text: d => d.length },\n { x: \"persecution_started\", interval: 'year', textAnchor: \"middle\", dy: -10, fill: \"black\" }\n )),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":636,"value":"\n \n \n \n \n \n \n \n \n \n \n \n ${criminalCasesDataFA.data.sort((b,a) => new Date(a.persecution_started) - new Date(b.persecution_started)).map(item => htl.html`\n \n \n \n \n \n \n `)}\n \n

Name	Age	Case	Article	Current location	Year
${item[\"name_en\"]}	${item[\"age\"]}	${item[\"case_name_en\"]}	${item[\"persecution_articles_criminal_code_en\"]}	${item[\"persecution_location_en\"]}	${item[\"persecution_started_year\"]}

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":621,"value":"## In relation to undesirable organisations legislation","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":818,"value":"According to OVD-Info there are at least ${criminalCasesDataUndesirable.data.length} criminal cases with the application of the article 284.1 of the Criminal Code for the breach of the undesirable organisations legislation. Below is the information about these cases. ","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":869,"value":"Plot.plot({\n color: { scheme: \"Paired\" },\n caption: `Number of criminal cases per year for carrying out the activities of an undesirable organization (article 284.1). ${criminalCasesDataUndesirable.data.filter(i => !i.persecution_started_year).length} cases are not shown in the graph because the year when the prosecution began is unknown.`,\n y: {\n grid: true,\n label: \"Number of cases\"\n },\n x: {\n label: \"Year\"\n },\n marks: [\n Plot.rectY(criminalCasesDataUndesirable.data, Plot.binX({y: \"count\"}, {x: \"persecution_started\", interval: 'year', fill: \"type\", tip: true})),\n Plot.text(criminalCasesDataUndesirable.data, Plot.binX(\n { y: \"count\", text: d => d.length },\n { x: \"persecution_started\", interval: 'year', textAnchor: \"middle\", dy: -10, fill: \"black\" }\n )),\n Plot.ruleY([0])\n ]\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":631,"value":"\n \n \n \n \n \n \n \n \n \n \n \n ${criminalCasesDataUndesirable.data.sort((b,a) => new Date(a.persecution_started) - new Date(b.persecution_started)).map(item => htl.html`\n \n \n \n \n \n \n `)}\n \n

Name	Age	Case	Article	Current location	Year
${item[\"name_en\"]}	${item[\"age\"]}	${item[\"case_name_en\"]}	${item[\"persecution_articles_criminal_code_en\"]}	${item[\"persecution_location_en\"]}	${item[\"persecution_started_year\"]}

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":5,"value":"# Available datasets","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":694,"value":"## Detailed data on foreign agents and undesirable organisations","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":652,"value":"[Detailed data](https://airtable.com/appUmJQnojJluh89V/shrrRISWxt2GW0rm7/tbl1f1pN3GJb1Xq4q) on foreign agents and undesirable organisations. Collected as part of the [Inoteka](https://inoteka.io/en) project.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":692,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":698,"value":"## Data on administrative cases","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":702,"value":"[Data](https://airtable.com/appUmJQnojJluh89V/shr7PNZrVPjBJQKal) on administrative cases related to foreign agents and undesirable organisations. This data is the collection of case profiles parsed from the websites of national courts (including judicial acts).\nThe dataset contains administrative cases on articles `19.34.1 part 1, 19.34.1 part 2, 19.34.1 part 3, 19.34 part 1, 19.34 part 3, 19.7.5-3 part 2, 19.34 part 2, 19.7.5-4 part 2, 19.34 part 4, 19.34 part 5, 19.34 part 8` for the period of 2022-2023 and on article `20.33` for the period of 2018-2023.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":707,"value":"","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":822,"value":"## Data on criminal cases","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":826,"value":"Data on relevant criminal cases available as part of OVD-Info's [dataset on political criminal persecutions](https://en.ovdinfo.org/data-politically-motivated-criminal-prosecutions-russia). This information is also available through [dedicated API](https://observablehq.com/d/3dfc2fcf987505cb).","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":687,"value":"***","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":7,"value":"entitiesRawData = fetch(\"https://static-data.ovd.info/foreign-agents-and-undesirables.json\")\n .then(response => {\n if (!response.ok) throw new Error(response.status);\n return response.json();\n })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":30,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":10,"value":"admCasesRawData = fetch(\"https://static-data.ovd.info/foreign-agents-and-undesirables-cases.json\")\n .then(response => {\n if (!response.ok) throw new Error(response.status);\n return response.json();\n })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":527,"value":"admCasesData = admCasesRawData.map(item => ({\n name: item['Ответчики'],\n registered: new Date(item['Дата поступления']),\n examined: item['Дата рассмотрения'] ? new Date(item['Дата рассмотрения']) : '',\n daysSinceRegistration: item['Дата рассмотрения'] && item['Дата поступления'] \n ? Math.round((new Date(item['Дата рассмотрения']).getTime() - new Date(item['Дата поступления']).getTime()) / (1000 * 3600 * 24)) \n : '',\n article: item['Статьи'],\n isForeignAgent: item['Статьи'].indexOf('20.33') === -1,\n isUndesirable: item['Статьи'].indexOf('20.33') > -1,\n gender: item['Gender'] ? item['Gender'] : 'unknown or n/a',\n penalty: item['Размер наказания'],\n decision: item['Decision type'] ? item['Decision type'] : 'Unknown or in progress',\n region: item['Region'],\n regionISO: item['Region (iso)'],\n instance: item['Инстанция']\n}))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":14,"value":"criminalCasesDataUndesirable = fetch('https://api.repression.info/v1/data?language=en&subset=full&filter={\"persecution_articles_criminal_code_number\":[\"284.1\"]}')\n .then(response => {\n if (!response.ok) throw new Error(response.status);\n return response.json();\n })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":21,"value":"criminalCasesDataFA = fetch('https://api.repression.info/v1/data?language=en&subset=full&filter={\"persecution_articles_criminal_code_number\":[\"330.1\"]}')\n .then(response => {\n if (!response.ok) throw new Error(response.status);\n return response.json();\n })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":278,"value":"russiaAndAnnexedRegionsRaw = FileAttachment(\"russia-and-annexed-regions-compressed.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":280,"value":"russiaAndAnnexedRegions = {\n const hiddenObjects = ['UA-14', 'UA-65', 'UA-09', 'UA-23']\n const filteredCollection = { type: \"GeometryCollection\", geometries: russiaAndAnnexedRegionsRaw.objects.collection.geometries.filter(g => hiddenObjects.indexOf(g.properties.iso) < 0) }\n return topojson.feature(russiaAndAnnexedRegionsRaw, filteredCollection)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":288,"value":"regionsIsoNameIndex = russiaAndAnnexedRegions.features.reduce((acc, r) => { acc[r.properties.iso] = r.properties.name_en; return acc }, {})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":661,"value":"import {note, try_it, details, box} from \"@observablehq/notes\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":666,"value":"import {toc} from \"@bryangingechen/toc\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"}],"files":"$W3c","stdlib":"1","titling":"auto"}} 31:"$30:body"