2a:null 2b:["$","title",null,{"children":"Language of Accidents | Miguel Vieira | Observable"}] 30:T6de,{ const dotTitle = (group) => { const firstYear = group[0].year; const titles = _.uniq(group.map((d) => d.title)).join("\n"); return `${firstYear}\n${titles}`; }; const arrowTitle = (d) => { const years = d.year; const shiftedTitles = shifted(d) .map( (d) => `${d.title}\nShifted from ${d.politicsShift.from} to ${d.politicsShift.to}` ) .join("\n\n"); return `${years}\n${shiftedTitles}`; }; const shifted = (source) => politicalShift.filter((obj) => Object.entries(source.politicsShift).every( ([key, value]) => obj.politicsShift[key] === value ) ); const plot = tooltipPlot().plot({ color: { domain: Object.keys(politicsDomain), legend: true, range: Object.values(politicsDomain) }, height: 300, inset: 10, marginLeft: calculateMarginLeft(sources, "politics"), marks: [ Plot.dot( _.orderBy(sources, ["year", "title"], "desc"), Plot.group( { r: "count", title: (group) => dotTitle(group) }, { x: "year", y: "politics", fill: "politics" } ) ), Plot.arrow(politicalShift, { x1: (d) => d.politicsShift.fromYear, y1: (d) => d.politicsShift.from, x2: (d) => d.politicsShift.toYear, y2: (d) => d.politicsShift.to, bend: true, headLength: 4, inset: 5, stroke: "#777", strokeWidth: 1.5, title: (d) => arrowTitle(d) }) ], r: { range: [1, 5] }, x: { tickFormat: (d) => formatYear(d), tickSize: 0 }, y: { tickSize: 0 }, width }); return plot; }31:T40a,### Subjects about accidents per year The plot below shows the relative frequencies of the annotations for each of the subjects in each year. Relative frequencies account for the variations in the year values and are calculated by dividing by the total number of subjects in that year. The **curves** in the plots below are created using a *[monotone-x](https://observablehq.com/plot/features/curves#curves)* curve, a curve interpolation method that ensures a smooth and monotonically increasing or decreasing curve when visualising data along the x-axis. The **trend line** (straight) in the plot represents the general direction or pattern of the annotation counts for that word per year. It is generated using linear regression. The **shaded area** in the plot represents the potential variability or imprecision in the data. The range is calculated using [confidence intervals for proportions](https://www.statology.org/confidence-interval-proportion/). The grey lines in the background represent the alternative annotations.32:T872,{ const victims = data.filter((v) => selectedVictimsStats.includes(v[victimsColourBy]) ); const color = {}; if (victimsColourBy === "politics") { color.domain = Object.keys(politicsDomain); color.range = Object.values(politicsDomain); } else if (domains[victimsColourBy]) { color.domain = Object.keys(domains[victimsColourBy]); color.range = Object.values(domains[victimsColourBy]); } const dodge = { x: (d, i) => d.year / 1000 + i, fy: victimsGroupBy, fill: victimsColourBy, title: (d) => `${d.year}, ${d.age}, ${d.gender}\n${victimsGroupBy}: ${d[victimsGroupBy]}\n${d.t}\n${d.annotation}` }; const mapX = (value, inputMin, inputMax, outputMin, outputMax) => { const inputRange = inputMax - inputMin; const outputRange = outputMax - outputMin; const normalizedValue = (value - inputMin) / inputRange; const mappedValue = Math.round(normalizedValue * outputRange + outputMin); return mappedValue; }; const plot = tooltipPlot().plot({ color, height: 400, inset: 10, marginLeft: calculateMarginLeft(victims, victimsGroupBy) + 10, marks: [ Plot.axisFy({ anchor: "left", fontSize: 12, fontWeight: "bold", label: null, lineWidth: 10 }), Plot.dot( victims, Plot.dodgeY("middle", { ...dodge, opacity: (d) => (d.year === yearScrubbedVictim ? 1 : 0.1) }) ), Plot.dot( victims, Plot.dodgeY("middle", { filter: (d) => d.year <= yearScrubbedVictim, ...dodge, opacity: (d) => yearScrubbedVictim === years[years.length - 1] ? 1 : 0.2 }) ) ], x: { axis: "bottom", tickFormat: (d) => formatYear(mapX(d, 0, data.length, years[0], years[years.length - 1])), tickSize: 0 }, width }); handlePlotClick(plot, victims, victims, "annotation", (title, sids) => { mutable selectedTitle = { ...selectedTitle, victims: title }; mutable selectedSids = { ...selectedSids, victims: sids }; }); return plot; }33:T857,{ const center = [-10, 55]; const height = 700; const land = topojson.feature(countries, countries.objects.countries); const features = geo.features.filter( (d) => d.properties.year <= yearGeo && (geoByLocation || selectedGeoDomains.includes(d.properties[geoGroupBy])) ); let color = { label: "Number of accidents:", legend: true, scheme: "Viridis" }; if (domains[geoGroupBy]) { color = { domain: Object.keys(domains[geoGroupBy]), range: Object.values(domains[geoGroupBy]) }; } const title = (d) => `${d.properties.place}, ${d.properties.loc}\n${d.properties.site}, ${d.properties.age}, ${d.properties.gender}`; const zoom = 0.3; const strokeWidth = 0.6; const plot = Plot.plot({ color, height, projection: d3 .geoMercator() .center(center) .scale(width * zoom), marks: [ Plot.geo(land, { fill: "#eee", stroke: "#999", strokeWidth }), Plot.dot( features, Plot.hexbin( { r: "proportion", stroke: geoByLocation ? "count" : undefined }, { x: (d) => d.geometry.coordinates[0], y: (d) => d.geometry.coordinates[1], stroke: (d) => geoByLocation ? undefined : d.properties[geoGroupBy], strokeWidth, tip: "xy", title } ) ) ], r: { range: [1, 10] }, width }); const plotContainer = d3.select(plot); const plotGroups = plotContainer.selectAll( "g[aria-label='dot'], g[aria-label='geo']" ); const tipGroup = plotContainer.select("g[aria-label='tip']"); d3.select(plot).call( d3 .zoom() .scaleExtent([0.9, 8]) .on("zoom", ({ transform }) => { plotContainer .selectAll("path") .attr("stroke-width", (d) => transform.k > 1 ? 1 / transform.k : transform.k - zoom ); plotGroups.attr("transform", transform); tipGroup.selectAll("*").attr("transform", transform); }) ); return plot; }34:Td2f,force = { // // Specify the dimensions of the chart. // const width = 928; // const height = 680; // // Specify the color scale. // const color = d3.scaleOrdinal(d3.schemeCategory10); // // The force simulation mutates links and nodes, so create a copy // // so that re-evaluating this cell produces the same result. // const nodes = network.nodes // .filter((d) => d.year === yearScrubbedNetwork) // .map((d) => ({ ...d })); // const nodeIds = nodes.map((d) => d.id); // const links = network.links // .filter((d) => nodeIds.includes(d.source) && nodeIds.includes(d.target)) // .map((d) => ({ ...d })) // .slice(0, 100); // // Create a simulation with several forces. // const simulation = d3 // .forceSimulation(nodes) // .force( // "link", // d3.forceLink(links).id((d) => d.id) // ) // .force("charge", d3.forceManyBody()) // .force("x", d3.forceX()) // .force("y", d3.forceY()); // // Create the SVG container. // const svg = d3 // .create("svg") // .attr("viewBox", [-width / 2, -height / 2, width, height]); // // Add a line for each link, and a circle for each node. // const link = svg // .append("g") // .attr("stroke", "#999") // .attr("stroke-opacity", 0.6) // .selectAll("line") // .data(links) // .join("line") // .attr("stroke-width", 1); // const node = svg // .append("g") // .attr("stroke", "#fff") // .attr("stroke-width", 1.5) // .selectAll("circle") // .data(nodes) // .join("circle") // .attr("r", 5) // .attr("fill", (d) => domains.age[d.age]); // node.append("title").text((d) => d.t); // // Add a drag behavior. // node.call( // d3.drag().on("start", dragstarted).on("drag", dragged).on("end", dragended) // ); // // Set the position attributes of links and nodes each time the simulation ticks. // simulation.on("tick", () => { // link // .attr("x1", (d) => d.source.x) // .attr("y1", (d) => d.source.y) // .attr("x2", (d) => d.target.x) // .attr("y2", (d) => d.target.y); // node.attr("cx", (d) => d.x).attr("cy", (d) => d.y); // }); // // Reheat the simulation when drag starts, and fix the subject position. // function dragstarted(event) { // if (!event.active) simulation.alphaTarget(0.3).restart(); // event.subject.fx = event.subject.x; // event.subject.fy = event.subject.y; // } // // Update the subject (dragged node) position during drag. // function dragged(event) { // event.subject.fx = event.x; // event.subject.fy = event.y; // } // // Restore the target alpha so the simulation cools after dragging ends. // // Unfix the subject position now that it’s no longer being dragged. // function dragended(event) { // if (!event.active) simulation.alphaTarget(0); // event.subject.fx = null; // event.subject.fy = null; // } // // When this cell is re-run, stop the previous simulation. (This doesn’t // // really matter since the target alpha is zero and the simulation will // // stop naturally, but it’s a good practice.) // invalidation.then(() => simulation.stop()); // return svg.node(); }35:T414,victims = getWorkflowAnnotations(victimsWorkflow.workflow_id) .map((a) => { const subject = victimsSubjects.find((s) => s.sid === a.sid); const source = sources.find((n) => n.nlp === subject?.nlp); return { ...a, subject, source }; }) .filter((a) => a.source) .map((a) => ({ sid: a.sid, annotation: a, details: { age: { ...a.T3, ...a.T6 }, gender: { ...a.T1, ...a.T4 } }, year: a.subject.year, t: a.subject.t, politics: a.source.politics, price: a.source.price, price_range: a.source.price_range })) .map((a) => { const age = _(a.details.age).toPairs().orderBy([1], ["desc"]).flatMap().value()[0] || ""; const gender = _(a.details.gender) .toPairs() .orderBy([1], ["desc"]) .flatMap() .value()[0] || ""; return { ...a, age: getAgeGroup(age), gender: getGender(gender) }; }) .map((a) => ({ ...a, annotation: JSON.stringify(a.details) })) .flatMap((a) => a.gender.map((g) => ({ ...a, gender: g })))36:T622,/** * Returns the age group based on the given age or age-related description. * * @param {string|number} age - The age or age-related description. * @returns {string} The age group corresponding to the given age. * Possible age groups: * - "children" (0-17 years old) * - "young adults" (18-25 years old) * - "adults" (26-65 years old) * - "elderly" (65+ years old) * - "mixed age groups" * - "unknown" (if the age cannot be determined) */ getAgeGroup = (age) => { const numericAge = parseInt(age, 10); if (!isNaN(numericAge)) { if (numericAge >= 18 && numericAge <= 25) { return "young adults"; } else if (numericAge > 25 && numericAge <= 65) { return "adults"; } else if (numericAge > 65) { return "elderly"; } else { return "children"; } } const lowerCaseAge = age.toLowerCase(); if ( lowerCaseAge.includes("child") || lowerCaseAge.includes("boy") || lowerCaseAge.includes("girl") ) { return "children"; } else if ( lowerCaseAge.includes("young") || lowerCaseAge.includes("youth") || lowerCaseAge.includes("lad") ) { return "young adults"; } else if (lowerCaseAge.includes("old") || lowerCaseAge.includes("elderly")) { return "elderly"; } else if (lowerCaseAge.includes("adult")) { return "adults"; } else if (lowerCaseAge.includes("mixed")) { return "mixed age groups"; } else { return "unknown"; } }37:T4b2,accidents = { const mapAnnotation = (value) => { if (value.indexOf("too hard to read") >= 0) { return "too hard to read"; } if (value.indexOf("no relevant articles") >= 0) { return "no relevant articles"; } if (value.indexOf("more than one") >= 0) { return "more than one article about accidents"; } if (value.indexOf("only one") >= 0) { return "one article about accidents"; } return value; }; return getWorkflowAnnotations(accidentsWorkflow.workflow_id) .filter((a) => a.T0) .map((a) => { const subject = accidentsSubjects.filter((s) => s.sid === a.sid)[0]; const source = newspapers[subject.nlp]; return { ...a, subject, source }; }) .filter((a) => a.source) .map((a) => { const t = Object.keys(a.T0)[0]; return { sid: a.sid, annotation: mapAnnotation(t), year: a.subject.year, politics: a.source.politics, price: a.source.price, price_range: a.source.price_range, lat: a.lat, lon: a.lon, loc: a.loc, dist: a.dist, nVictims: a.n_victims, nBodyParts: a.n_body_parts }; }); }38:[{"id":"0c0c4742be9452299388dc97f0618b26b54630191b32b7d0a9744170cd86a162744701770c6ae2ad3bed982480972c83ad197ac299d736911709b4210904b820","href":"https://static.observableusercontent.com/files/0c0c4742be9452299388dc97f0618b26b54630191b32b7d0a9744170cd86a162744701770c6ae2ad3bed982480972c83ad197ac299d736911709b4210904b820","name":"DAVIZCT-workflow.jpg","type":"image/jpeg","lastModified":1689008912877.645,"size":862631},{"id":"7c6167b65013c12f3978b4d8e85dd28a27e3b5eb580d1e76696ce5b0d399c196de2b02c45e734462931e1af823698e36bb072722253d5e03e7fb61222755bc0c","href":"https://static.observableusercontent.com/files/7c6167b65013c12f3978b4d8e85dd28a27e3b5eb580d1e76696ce5b0d399c196de2b02c45e734462931e1af823698e36bb072722253d5e03e7fb61222755bc0c","name":"countries-110m.json","type":"application/json","lastModified":1688849079133.237,"size":107761},{"id":"1858850bb9b642b10e259c7f5f1e4da356d2cb12182e76572a1b825f8cbdbddb2a33f7a30e2a110a85fcdc055f287f5f69e3f9e1f701a5d6c0fc851e72a466e2","href":"https://static.observableusercontent.com/files/1858850bb9b642b10e259c7f5f1e4da356d2cb12182e76572a1b825f8cbdbddb2a33f7a30e2a110a85fcdc055f287f5f69e3f9e1f701a5d6c0fc851e72a466e2","name":"Artboard 1_3.png","type":"image/png","lastModified":1688983347656.178,"size":105226}] 2e:{"id":"63e00b1624bc6a06","slug":"lwm-language-of-accidents","title":"Language of Accidents","thumbnail":"588d7321f685b97b01848d38c5e82d8a78a803ad4e8090c365ea736907df2b00","access_level":"public","create_time":"$D2023-04-28T16:46:49.221Z","update_time":"$D2025-03-04T14:38:16.959Z","view_time":null,"first_public_time":"$D2023-04-28T16:46:49.221Z","fork":false,"stars":1,"starred":false,"owner":{"type":"team","id":"587db768fa766a06","login":"jmiguelv","name":"Miguel Vieira","avatar_url":"https://avatars-next.observableusercontent.com/4fba40b1cfe58889e137e945ed99c3eef4bd8f6f4585d123d0288455e42e1195","tier":"starter_2024"},"version":5188,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"8ed700ef90ca11f2","login":"jmiguelv","name":"Miguel Vieira","avatar_url":"https://avatars-next.observableusercontent.com/4fba40b1cfe58889e137e945ed99c3eef4bd8f6f4585d123d0288455e42e1195","tier":null}],"members":[{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null,"role":"editor"},{"type":"individual","id":"8ed700ef90ca11f2","login":"jmiguelv","name":"Miguel Vieira","avatar_url":"https://avatars-next.observableusercontent.com/4fba40b1cfe58889e137e945ed99c3eef4bd8f6f4585d123d0288455e42e1195","tier":null,"role":"editor"},{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null,"role":"editor"},{"type":"individual","id":"8ae44428717bed65","login":"ongtiffany","name":"Tiffany Ong","avatar_url":"https://avatars-next.observableusercontent.com/90bb82ebec84e2a6c0c37b437ab558ae373abc2059b6c334a1b176809bc79a50","tier":null,"role":"editor"}],"comments":[{"id":"201637f8fdcda157","reply_to_id":null,"content":"I've made an assumption here! This also makes me wonder whether all our titles in Zooniverse can be matched to Mitchell's records, and what happens to those that can't be matched?","create_time":"$D2023-05-16T09:03:17.334Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"b1e67092891a5820","reply_to_id":null,"content":"The exact phrasing of some of these classification options might have changed over time (e.g. a word or punctuation change). Are like options grouped together regardless?","create_time":"$D2023-05-16T09:04:52.810Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"058e4f7cc96380e2","reply_to_id":null,"content":"I love this subjects access! Should it only include items from the matching workflow e.g. in this case How did machines change accidents?","create_time":"$D2023-05-16T09:06:23.156Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"a71a7abe23e4602f","reply_to_id":"058e4f7cc96380e2","content":"It'd be great to repeat this for the 'detail' tasks, as that's where it really starts to inspire curiosity","create_time":"$D2023-05-16T09:18:04.552Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"dfb0eeb83c2e01b8","reply_to_id":null,"content":"Is the idea that we'd add highlights via the code to point out shifts in various aspects?","create_time":"$D2023-05-16T09:19:00.905Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"407453f0371b0f46","reply_to_id":null,"content":"Is gbp here grouped into relative buckets (e.g. cheaper, more expensive) or literal? With inflation, I assume all prices would shift upwards...","create_time":"$D2023-05-16T09:20:21.609Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"0a12d6c0a2e7c8c6","reply_to_id":null,"content":"Some of the tooltips have different values than the key above e.g. on road, 1872 there's 'democratic, anti-poor law'","create_time":"$D2023-05-16T09:24:54.908Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"affaaca9168f4d23","reply_to_id":null,"content":"Thank you for suggesting the date, it is something I have been meaning to add.","create_time":"$D2023-05-16T09:29:19.508Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"8ed700ef90ca11f2","login":"jmiguelv","name":"Miguel Vieira","avatar_url":"https://avatars-next.observableusercontent.com/4fba40b1cfe58889e137e945ed99c3eef4bd8f6f4585d123d0288455e42e1195","tier":null}},{"id":"11f29eaea92ba970","reply_to_id":"201637f8fdcda157","content":"At the moment it is all from MPD.","create_time":"$D2023-05-16T09:33:36.473Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"8ed700ef90ca11f2","login":"jmiguelv","name":"Miguel Vieira","avatar_url":"https://avatars-next.observableusercontent.com/4fba40b1cfe58889e137e945ed99c3eef4bd8f6f4585d123d0288455e42e1195","tier":null}},{"id":"d25aa07189bfda2a","reply_to_id":"201637f8fdcda157","content":"It's fine if it all comes from Mitchell's at this point","create_time":"$D2023-05-16T09:55:26.556Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"9e1fbf91d43fa8ae","reply_to_id":"201637f8fdcda157","content":"We might need an 'information not available' option where we want to show records that aren't in MPD - if there are any?","create_time":"$D2023-05-16T09:56:17.943Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"51cd6e349fa23e12","reply_to_id":"dfb0eeb83c2e01b8","content":"Shifts in e.g. price point related to stamp duty changes","create_time":"$D2023-05-16T10:08:19.450Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"a2957e647e42d86d","reply_to_id":null,"content":"Mia to add explanation of what active and non active mean","create_time":"$D2023-05-16T11:20:48.816Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null}},{"id":"0a05b65666a5208e","reply_to_id":null,"content":"Proposed to change tooltip to simplify reading: \n\nHard to read\nNo accidents\n> 1 article on accidents\n1 article on accidents","create_time":"$D2023-05-16T12:00:12.039Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null}},{"id":"732df18b6363d2dd","reply_to_id":"0a05b65666a5208e","content":"Agreed via slack to add to Key only","create_time":"$D2023-05-16T17:43:26.770Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null}},{"id":"322b08f6a688913b","reply_to_id":null,"content":"Mia or others in LWM wider project team to add explanation of how political groupings are created?","create_time":"$D2023-05-23T11:54:51.148Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null}},{"id":"733d0607a3e596af","reply_to_id":"407453f0371b0f46","content":"Literal value (lower when multiple values exist as agreed)","create_time":"$D2023-05-23T11:58:23.611Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null}},{"id":"9b04e7b4807c61da","reply_to_id":"affaaca9168f4d23","content":"We don't have 78,030 plus 9,116 participants :D I assume the data should look at the count of distinct volunteer IDs?","create_time":"$D2023-05-23T16:11:38.596Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"5adc5d876932629f","reply_to_id":"322b08f6a688913b","content":"I've done a first pass but I'm sure others on the project can improve it!","create_time":"$D2023-05-23T16:19:21.813Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"189dd92033c1c867","reply_to_id":"affaaca9168f4d23","content":"🤦 it should be fixed.","create_time":"$D2023-05-24T06:33:51.253Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"8ed700ef90ca11f2","login":"jmiguelv","name":"Miguel Vieira","avatar_url":"https://avatars-next.observableusercontent.com/4fba40b1cfe58889e137e945ed99c3eef4bd8f6f4585d123d0288455e42e1195","tier":null}},{"id":"9ee6681b945ae18f","reply_to_id":"322b08f6a688913b","content":"Thanks. What I meant was also that out of all political parties categories in the directory (environmental scan) you then grouped those further - do you need/want to specify how that grouping was done?","create_time":"$D2023-05-24T10:22:08.697Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null}},{"id":"1b91e171cbee7d1f","reply_to_id":null,"content":"Explain what 'subjects' are","create_time":"$D2023-05-30T09:19:48.011Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"13b7cd0ffd6e4a92","login":"mialondon","name":"Mia","avatar_url":"https://avatars-next.observableusercontent.com/718fd54635137cd9a35241d6876cfe3ece957358071d65ea1440f3a156a753a4","tier":null}},{"id":"d5b3b0240cbbfec8","reply_to_id":null,"content":"Year format to be changed (remove commas)","create_time":"$D2023-05-30T15:25:04.901Z","update_time":null,"resolved":true,"user":{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null}},{"id":"50e7e18ec681dab0","reply_to_id":null,"content":"useful to add a description of what it is meant by mixed gender here Mia?","create_time":"$D2023-09-11T08:23:46.058Z","update_time":null,"resolved":false,"user":{"type":"individual","id":"b2ec398dbbfd640d","login":"aciula","name":"Arianna Ciula","avatar_url":"https://avatars-next.observableusercontent.com/57b045e4ad74d8a896a5152d0f0726fb2b1f1acd5b126df478c14298878c86cd","tier":null}}],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":2,"collection":null,"type":"notebook","body":{"title":"Language of Accidents","cells":[{"id":0,"value":"# Language of Accidents","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":2161,"value":"disclaimer()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3843,"value":"livingWithMachines","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3846,"value":"A key research strand, designed from the beginning to include public contributions, investigated [how machines changed accidents](https://www.zooniverse.org/projects/bldigital/living-with-machines/talk/2795/2699884). We built crowdsourcing tasks on the Zooniverse citizen science platform in combination with data science and machine learning methods to find new insights within the pages of historical newspapers. This page focuses on data collected for this research. It visualises data from the original digitised newspaper articles, contemporary press directories that described individual newspapers, and classifications by Zooniverse volunteers.\n\nThe notebook, designed and developed by our colleagues from [King's Digital Lab](https://kdl.kcl.ac.uk/projects/living-with-machines/) (Miguel Vieira, Tiffany Ong and Arianna Ciula), begins with an overview then has options to filter data and allow more exploration.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":3850,"value":"toc()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3859,"value":"## What were the Data Sources?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":3862,"value":"aboutTheData(\"How did machines change accidents?\", totalNumberOfSubjects)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3865,"value":"alert(\n \"Note\",\n `The data used in this notebook was exported / uploaded at ${dataExportDate}.`\n)\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3875,"value":"## Who were the Contributors?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":3877,"value":"There were ${(participantsBreakdown.loggedIn + participantsBreakdown.notLoggedIn).toLocaleString()} individual contributors that used the Zooniverse platform. Just under half (${participantsBreakdown.notLoggedIn.toLocaleString()}) did not log into a Zooniverse account - this shows the value of allowing users to contribute without an account.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":194,"value":"workflowsParticipantsPlot(projectParticipants)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3885,"value":"alert(\"Note\", \"We'd like to thank all our contributors for their classifications, transcriptions, questions and comments!\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3892,"value":"## What were the Workflows and Annotations?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":3894,"value":"In Zooniverse, the contributors were asked to perform a group of tasks (**workflows**) of which there were 4:\n- ${workflows.map((w) => `[${w.display_name}](#${workflowSlug(w.display_name)})`).join(\"\\n- \")}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4898,"value":"artboard1_3 = FileAttachment(\"DAVIZCT-workflow.jpg\").image({\n width: width / 1.5\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3913,"value":"The bar chart below shows the number of subjects each year from ${_.minBy(subjects, \"year\").year} to ${_.maxBy(subjects, \"year\").year}, and can be coloured by workflow. The years, ${getSubjectTopYears(2).join(\" and \")}, have the most subjects in the data.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":2441,"value":"viewof toggleSubjectsColour = Inputs.toggle({\n label: \"Colour by workflow\",\n value: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2387,"value":"toggleSubjectsColour\n ? subjectsPlot(subjects, \"workflow\")\n : subjectsPlot(subjects)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3992,"value":"Each workflow had a number of tasks which the contributors were asked to complete by subject classification (**annotations**). In total there were ${totalNumberOfAnnotations.toLocaleString()} annotations over ${totalNumberOfSubjects.toLocaleString()} subjects across the ${workflows.length} workflows.\n\n${activeStatusDescription}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":34,"value":"workflowsAnnotationsPlot(workflows)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4008,"value":"## What were the newspapers like?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4012,"value":"All data points come from Mitchells Press Directories information processed by the Living with Machines project.\n\nLooking more in depth into the newspapers' data, we can compare the price range, political leaning, their locations and year publication...","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1091,"value":"### Overview of Political groups\nOverview of political leaning for newspaper titles according to [Mitchell's Press Directories](https://en.wikipedia.org/wiki/Mitchell%27s_Press_Directories), a contemporary source that noted the politics of a newspaper title and its proprietors.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1033,"value":"newspapersPoliticalDistribution(getNewspapersPoliticalDistribution())","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1088,"value":"### Political groups of the `${projectTitle}` workflows \nThis project worked with digitised newspapers in the public domain, a proportion of digitised newspapers available on the British Newspaper Archive, which is a proportion of all newspapers published.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1588,"value":"newspapersPoliticalDistribution(sourcesPolitics, politicsDomain)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3512,"value":"### Political shifts\nOf the ${_.uniqBy(sources, \"chain_id\").length} newspapers used in the _${projectTitle}_, ${politicalShift.length} changed political leaning:\n- ${politicalShift\n .map(\n (p) =>\n `${p.title} ${p.politicsShift.from} ${\n p.politicsShift.fromYear\n } ➔ ${\n p.politicsShift.to\n } ${p.politicsShift.toYear}`\n )\n .join(\"\\n- \")}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":3279,"value":"$30","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4014,"value":"### Prices\n*[Details of price buckets?]* Over time, newspapers became cheaper, possibly due to the rise in.....","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4018,"value":" Select the different options below to view the different data dimensions.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":292,"value":"viewof sourcesGroupBy = Inputs.radio(\n [\"county\", \"politics\", \"price\", \"price_range\", \"title\", \"year\"],\n {\n label: \"Group by:\",\n value: \"politics\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":321,"value":"viewof sourcesColourBy = Inputs.radio(\n [\"county\", \"politics\", \"price\", \"price_range\", \"year\"],\n {\n label: \"Colour by:\",\n value: \"price_range\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":216,"value":"sourcesColourBy === \"politics\"\n ? newspapersPlot(sources, sourcesGroupBy, sourcesColourBy, politicsDomain)\n : newspapersPlot(sources, sourcesGroupBy, sourcesColourBy)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4095,"value":"## The Language of Accidents workflows","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":406,"value":"## `${accidentsWorkflow.display_name}`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":515,"value":"$31","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1897,"value":"subjectsTable(\n selectedTitle.accidents,\n accidentsSubjects,\n selectedSids.accidents\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1818,"value":"viewof selectedAccidents = interactiveLegend(Object.keys(domains.accidents), {\n range: Object.values(domains.accidents)\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3061,"value":"{\n const data = accidentsPerYear.filter((a) =>\n selectedAccidents.includes(a.annotation)\n );\n\n const plot = facetedLinePlot(data, {\n x: \"year\",\n y: \"count\",\n fy: \"annotation\",\n xDomain: [\n _.minBy(accidentsPerYear, \"year\").year,\n _.maxBy(accidentsPerYear, \"year\").year\n ],\n fyDomain: domains.accidents,\n title: (d) => `${d.annotation}, ${d.year}\\n${d3.format(\".2%\")(d.count)}`,\n r: \"count\",\n showConfidenceInterval: false,\n showLinearRegression: true\n });\n\n handlePlotClick(plot, data, accidents, \"annotation\", (title, sids) => {\n mutable selectedTitle = {\n ...selectedTitle,\n accidents: title\n };\n mutable selectedSids = {\n ...selectedSids,\n accidents: sids\n };\n });\n\n return plot;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1689,"value":"## `${sitesWorkflow.display_name}`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":629,"value":"### Annotations per site per year","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":660,"value":"viewof selectedSites = interactiveLegend(Object.keys(domains.site), {\n range: Object.values(domains.site)\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1906,"value":"subjectsTable(selectedTitle.sites, sitesSubjects, selectedSids.sites)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2581,"value":"{\n const data = sitesPerYear.filter((s) => selectedSites.includes(s.site));\n const domain = Object.fromEntries(\n Object.entries(domains.site).filter(([k, v]) => selectedSites.includes(k))\n );\n\n const plot = ridgelinePlot(data, {\n x: \"year\",\n xDomain: [\n _.minBy(sitesPerYear, \"year\").year,\n _.maxBy(sitesPerYear, \"year\").year\n ],\n y: \"count\",\n fy: \"site\",\n domain,\n normalise: true,\n overlap: 2,\n sort: \"year\",\n title: (d) => `${d.site}, ${d.year}\\n${d.count}`\n });\n\n handlePlotClick(plot, data, sites, \"site\", (title, sids) => {\n mutable selectedTitle = {\n ...selectedTitle,\n sites: title\n };\n mutable selectedSids = {\n ...selectedSids,\n sites: sids\n };\n });\n\n return plot;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":812,"value":"### Annotations per site per year, coloured by `${sitesColourBy}`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":818,"value":"viewof sitesColourBy = Inputs.radio([\"politics\", \"price_range\"], {\n label: \"Colour by:\",\n value: \"politics\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":716,"value":"{\n const color = { legend: true };\n if (sitesColourBy === \"politics\") {\n color.domain = Object.keys(politicsDomain);\n color.range = Object.values(politicsDomain);\n } else if (domains[sitesColourBy]) {\n color.domain = Object.keys(domains[sitesColourBy]);\n color.range = Object.values(domains[sitesColourBy]);\n }\n\n return Plot.plot({\n color,\n height: 400,\n inset: 10,\n marginLeft: calculateMarginLeft(sites, \"site\"),\n marks: [\n Plot.dot(\n sites,\n Plot.group(\n { r: \"proportion\" },\n {\n x: \"year\",\n y: \"site\",\n stroke: sitesColourBy,\n tip: \"xy\"\n }\n )\n )\n ],\n width,\n r: { range: [1, 10] },\n x: { tickFormat: (d) => formatYear(d) },\n y: { domain: Object.keys(domains.site), grid: true, label: \"Accidents\" }\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2145,"value":"## `${victimsWorkflow.display_name}`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":3225,"value":"viewof victimsGroupBy = Inputs.radio([\"age\", \"gender\", \"politics\", \"site\"], {\n label: \"Group by:\",\n value: \"gender\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2367,"value":"viewof victimsColourBy = Inputs.radio([\"age\", \"gender\", \"politics\", \"site\"], {\n label: \"Colour by:\",\n value: \"gender\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2914,"value":"viewof selectedVictimsStats = {\n const domain =\n victimsColourBy === \"politics\" ? politicsDomain : domains[victimsColourBy];\n return interactiveLegend(Object.keys(domain), {\n range: Object.values(domain)\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3756,"value":"viewof yearScrubbedVictim = Scrubber(years, {\n delay: 1000 / 48,\n loop: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2322,"value":"subjectsTable(selectedTitle.victims, victimsSubjects, selectedSids.victims)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2114,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2978,"value":"### Age by site coloured by gender","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":3671,"value":"viewof yearScrubbedSiteGender = Scrubber(years, {\n delay: 1000 / 48,\n loop: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3712,"value":"viewof selectedVictimsGender = interactiveLegend(Object.keys(domains.gender), {\n range: Object.values(domains.gender)\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2932,"value":"{\n const victims = data\n .filter((d) => d.year <= yearScrubbedSiteGender)\n .filter((v) => selectedVictimsGender.includes(v.gender));\n const ageDomain = victims.map((v) => v.age);\n const siteDomain = victims.map((v) => v.site);\n\n return Plot.plot({\n color: {\n domain: Object.keys(domains.gender),\n range: Object.values(domains.gender)\n },\n height: 400,\n marginLeft: calculateMarginLeft(data, \"site\"),\n marks: [\n Plot.dot(\n victims,\n Plot.group(\n { r: \"proportion\" },\n {\n x: \"age\",\n y: \"site\",\n stroke: \"gender\",\n tip: \"xy\"\n }\n )\n )\n ],\n x: {\n domain: Object.keys(domains.age),\n tickRotate: 0\n },\n y: {\n domain: Object.keys(domains.site)\n },\n width\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3009,"value":"### Explore the accidents","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":2989,"value":"viewof xFacet = Inputs.radio([\"age\", \"gender\", \"site\"], {\n label: \"Select X\",\n value: \"age\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2991,"value":"viewof yFacet = Inputs.radio([\"age\", \"gender\", \"site\"], {\n label: \"Select Y\",\n value: \"gender\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2981,"value":"{\n return Plot.plot({\n color: {\n legend: true,\n scheme: \"Reds\"\n },\n marginLeft: calculateMarginLeft(victims, yFacet) + 75,\n marks: [\n Plot.cell(\n data,\n Plot.group(\n { fill: \"proportion\" },\n {\n x: xFacet,\n y: yFacet,\n stroke: defaultColour,\n tip: \"xy\"\n }\n )\n )\n ],\n x: { domain: Object.keys(domains[xFacet]), tickRotate: 0 },\n y: { domain: Object.keys(domains[yFacet]) },\n width\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3041,"value":"## `${placesWorkflow.display_name}`\nThe map below shows the locations where accidents happened. Most accident reports were local to the UK, but there are quite a few cases where the accidents happened quite far away from the location of reporting.\n\nThe top five accidents furthest from the report location were:\n\n1. ${dataByDist.filter((d) => d.year <= yearGeo).slice(0, 5).map((d) => `${d.year}, ${d.loc}, [_${d.t}_](${subjects.find((s) => s.sid === d.sid)?.img}); ${d.dist.toLocaleString()}km`).join(\"\\n1. \")}\n\nQuite a lot of the accidents involved machinery and turned out to be quite gruesome, this are the top five:\n\n1. ${dataByBodyParts.filter((d) => d.year <= yearGeo).slice(0, 5).map((d) => `${d.year}, ${d.loc}, [_${d.t}_](${subjects.find((s) => s.sid === d.sid)?.img}); ${d.nVictims} victim, ${d.nBodyParts} body parts`).join(\"\\n1. \")}","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4541,"value":"viewof yearGeo = Scrubber(geoYears, {\n delay: 1000 / 48,\n loop: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4553,"value":"viewof geoGroupBy = Inputs.radio(\n [\"age\", \"gender\", \"location\", \"politics\", \"site\"],\n {\n label: \"Group by:\",\n value: \"location\"\n }\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4738,"value":"viewof selectedGeoDomains = geoByLocation\n ? Inputs.checkbox({ disabled: true })\n : interactiveLegend(Object.keys(domains[geoGroupBy]), {\n range: Object.values(domains[geoGroupBy])\n })","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4312,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4217,"value":"## Network","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4259,"value":"viewof yearScrubbedNetwork = Scrubber(years, {\n autoplay: false,\n delay: 1000 / 48,\n loop: false\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4154,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4097,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4122,"value":"observable","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4124,"value":"accessibility()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4132,"value":"---","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4129,"value":"## The code\nThis section below is the code used to generate the charts above. They are part of Observable's way of making notebooks allowing the more technical to dive into it, but can be ignored by everyone else.","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1229,"value":"### Views","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":1449,"value":"mutable selectedTitle = ({ accidents: \"\", sites: \"\", victims: \"\" })","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1134,"value":"mutable selectedSids = ({ accidents: [], sites: \"\", victims: \"\" })","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":65,"value":"### Data","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4174,"value":"network = {\n function getLinks(data) {\n const links = [];\n const properties = [\"age\"];\n\n data\n .sort((a, b) => a.year - b.year)\n .forEach((source, index) => {\n data.slice(index + 1).find((target) => {\n const sharedProperties = properties.every(\n (property) => source[property] === target[property]\n );\n\n if (sharedProperties) {\n links.push({ source: source.sid, target: target.sid });\n // return true;\n }\n });\n });\n\n return links;\n }\n\n return {\n nodes: data.map((d) => ({ ...d, id: d.sid })),\n links: getLinks(data).slice(10),\n allLinks: getLinks(data)\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4814,"value":"geoByLocation = geoGroupBy === \"location\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4722,"value":"geoYears = [\n ...new Set(geo.features.map((d) => d.properties.year).sort((a, b) => a - b))\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4287,"value":"geo = ({\n type: \"FeatureCollection\",\n features: data\n .filter((d) => d.lat)\n .map((d) => ({\n type: \"Feature\",\n geometry: { type: \"Point\", coordinates: [d.lon, d.lat] },\n properties: {\n loc: d.loc,\n year: d.year,\n site: d.site,\n age: d.age,\n gender: d.gender,\n place: d.place,\n politics: d.politics\n }\n }))\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3621,"value":"years = [...new Set(data.map((d) => d.year).sort((a, b) => a - b))]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5101,"value":"dataByBodyParts = data\n .filter((d) => d.nVictims)\n .sort((a, b) => b.nBodyParts - a.nBodyParts)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5098,"value":"dataByDist = data.filter((d) => d.nVictims).sort((a, b) => b.dist - a.dist)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2575,"value":"data = victims\n .map((victim) => {\n const accident = accidents.find((a) => a.sid === victim.sid);\n const site = sites.find((s) => s.sid === victim.sid);\n const place = places.find((p) => p.sid === victim.sid);\n\n return {\n ...victim,\n ...site,\n ...place,\n lat: accident?.lat,\n lon: accident?.lon,\n loc: accident?.loc,\n dist: accident?.dist,\n nVictims: accident?.nVictims,\n nBodyParts: accident?.nBodyParts\n };\n })\n .sort((a, b) => a.year - b.year)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2485,"value":"#### `${placesWorkflow.display_name}`\nThe place names are too varied, and at vary different levels, has there been any mapping done by the project?","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":4706,"value":"countries = FileAttachment(\"countries-110m.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2515,"value":"placesUnique = [\n ...new Set(\n places\n .map((p) => p.place.replace(/^\\d+\\s*/, \"\").replace(/\\s*\$.*?\$/, \"\"))\n .filter((p) => p)\n )\n].sort()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2498,"value":"places = getWorkflowAnnotations(placesWorkflow.workflow_id)\n .map((a) => {\n const subject = placesSubjects.find((s) => s.sid === a.sid);\n const source = sources.find((n) => n.nlp === subject?.nlp);\n\n return { ...a, subject, source };\n })\n .filter((a) => a.source)\n .map((a) => ({\n sid: a.sid,\n annotation: a,\n details: { place: a.T0 || \"unknown\", type: a.T1 },\n year: a.subject.year,\n t: a.subject.t,\n politics: a.source.politics,\n price: a.source.price,\n price_range: a.source.price_range\n }))\n .map((a) => {\n const place =\n _(a.details.place)\n .toPairs()\n .orderBy([1], [\"desc\"])\n .flatMap()\n .value()[0] || \"\";\n const type =\n _(a.details.type).toPairs().orderBy([1], [\"desc\"]).flatMap().value()[0] ||\n \"\";\n\n return {\n ...a,\n place,\n type\n };\n })\n .map((a) => ({ ...a, annotation: JSON.stringify(a.details) }))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2493,"value":"placesSubjects = getSubjects(placesWorkflow.workflow_id)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2487,"value":"placesWorkflow = getWorkflow(23457)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2131,"value":"#### `${victimsWorkflow.display_name}`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":2063,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2796,"value":"getGender = (value) => {\n if (value.indexOf(\"female\") >= 0) {\n return [\"female\"];\n }\n\n if (value.indexOf(\"male\") >= 0) {\n return [\"male\"];\n }\n\n if (value.indexOf(\"equal\") >= 0) {\n return [\"mixed gender groups\"];\n }\n\n return [\"unknown\"];\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2353,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2058,"value":"victimsSubjects = getSubjects(victimsWorkflow.workflow_id)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2054,"value":"victimsWorkflow = getWorkflow(18831)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1376,"value":"#### `${sitesWorkflow.display_name}`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":551,"value":"sitesPerYear = Object.values(\n sites.reduce((acc, cur) => {\n const key = `${cur.site}-${cur.year}`;\n\n if (!acc[key]) {\n acc[key] = { site: cur.site, year: cur.year, count: 0 };\n }\n\n acc[key][\"count\"] += 1;\n\n return acc;\n }, {})\n).sort((a, b) => a.year - b.year)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":539,"value":"sites = getWorkflowAnnotations(sitesWorkflow.workflow_id)\n .filter((a) => a.T0)\n .map((a) => {\n const subject = sitesSubjects.find((s) => s.sid === a.sid);\n const source = sources.find((n) => n.nlp === subject?.nlp);\n\n return { ...a, subject, source };\n })\n .filter((a) => a.source)\n .map((a) => ({\n sid: a.sid,\n site: Object.keys(a.T0).at(-1).split(\":\")[0].split(\" /\")[0],\n year: a.subject.year,\n politics: a.source.politics,\n price: a.source.price,\n price_range: a.source.price_range\n }))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":536,"value":"sitesSubjects = getSubjects(sitesWorkflow.workflow_id)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":533,"value":"sitesWorkflow = getWorkflow(21525)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1379,"value":"#### `${accidentsWorkflow.display_name}`","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":483,"value":"accidentsPerYear = normaliseCountsByYear(\n Object.values(\n accidents.reduce((acc, cur) => {\n const key = `${cur.annotation}-${cur.year}`;\n\n if (!acc[key]) {\n acc[key] = { annotation: cur.annotation, year: cur.year, count: 0 };\n }\n\n acc[key][\"count\"] += 1;\n\n return acc;\n }, {})\n )\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":374,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":418,"value":"accidentsSubjects = getSubjects(accidentsWorkflow.workflow_id)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":372,"value":"accidentsWorkflow = getWorkflow(20921)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1381,"value":"#### Newspapers","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":3813,"value":"politicsDomain = Object.fromEntries(\n Object.entries(domains.politics).filter(([key]) =>\n sourcesPolitics.map((s) => s.politics).includes(key)\n )\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1983,"value":"politicalShift = getNewspapersPoliticalShift(sources).flatMap((d) => d.details)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1590,"value":"sourcesPolitics = getNewspapersPoliticalDistribution(sources)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":204,"value":"sources = getNewspapers(nlps)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1755,"value":"newspapers = getNewspapers()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1383,"value":"#### Project","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":114,"value":"participantsBreakdown = getParticipantsBreakdown(workflows)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":131,"value":"projectParticipants = workflows.flatMap((w) => getParticipants(w.workflow_id))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":96,"value":"totalNumberOfSubjects = [...new Set(subjects.map((s) => s.sid))].length","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":91,"value":"totalNumberOfAnnotations = workflows.reduce((acc, cur) => acc + cur.classifications_count, 0)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":980,"value":"nlps = [...new Set(subjects.map((s) => s.nlp))]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3249,"value":"normaliseCountsByYear = (data) =>\n data\n .map((a) => ({ ...a, count: a.count / getNumberOfSubjectsForYear(a.year) }))\n .sort((a, b) => a.year - b.year)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3237,"value":"getNumberOfSubjectsForYear = (year) =>\n subjects.filter((s) => s.year === year).length","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3919,"value":"getSubjectTopYears = (n = 2) => {\n return _(subjects)\n .countBy(\"year\")\n .entries()\n .sort((a, b) => b[1] - a[1])\n .slice(0, n)\n .map(([year, _]) => Number(year))\n .value();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":977,"value":"subjects = workflows\n .flatMap((w) => [...getSubjects(w.workflow_id)])\n .map((s) => ({ ...s, workflow: getWorkflow(s.workflow_id).display_name }))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":22,"value":"workflows = project.workflows\n .map((w) => getWorkflow(w.workflow_id))\n .sort((a, b) =>\n a.display_name.startsWith(\"How\") ? -1 : a.workflow_id - b.workflow_id\n )","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":13,"value":"project = getProject(projectTitle)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":11,"value":"projectTitle = \"Language of Accidents\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1385,"value":"### Dependencies","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined"},{"id":2159,"value":"import {\n aboutTheDataAccidents as aboutTheData,\n accessibility,\n activeStatusDescription,\n alert,\n participantsDescription,\n disclaimer,\n livingWithMachines,\n observable,\n toc,\n workflowSlug\n} from \"@jmiguelv/lwm-backend-text\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1730,"value":"import {\n calculateMarginLeft,\n defaultColour,\n domainComparator,\n domains,\n facetedLinePlot,\n formatYear,\n handlePlotClick,\n interactiveLegend,\n newspapersPlot,\n newspapersPoliticalDistribution,\n politicalShiftPlotMarks,\n ridgelinePlot,\n subjectsPlot,\n subjectsTable,\n tooltipPlot,\n workflowsAnnotationsPlot,\n workflowsParticipantsPlot\n} from \"@jmiguelv/lwm-backend-plotting\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":202,"value":"import {\n getNewspapers,\n getNewspapersPoliticalDistribution,\n getNewspapersPoliticalShift\n} from \"@jmiguelv/lwm-backend-data\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5,"value":"import {\n dataExportDate,\n getParticipants,\n getParticipantsBreakdown,\n getProject,\n getSubjects,\n getWorkflow,\n getWorkflowAnnotations\n} from \"@jmiguelv/lwm-backend-data\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3609,"value":"import { Scrubber } from \"@mbostock/scrubber\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"}],"files":"$W38","stdlib":"1","titling":"auto"}} 2f:"$2e:body"