2d:null 2e:["$","title",null,{"children":"DEI & University | Mark Woosey | Observable"}] 33:T52d,md`# DEI & University **N.B.**: The visualisations are still a work in progress and may have some bugs in rendering the data/how different groups are differentiated. Forking is encouraged to tailor the visualisations to your organisation's specific areas of interest. **If viewing on a mobile device, rotate your device horizontally to avoid rendering issues with labels.** All data regarding student demographics provided by [HESA]. Data surrounding institute _ranking_ is from [The Guardian's University Guide][grauniad uni]. Categorisation of Russell Group universities provided by [The Russell Group][Russell]. Athena Swan Award status from [Advance HE][Swan]. _As awards are typically awarded to departments or faculties, the specific categorisation is a best-guess attempt to align faculties with subjects corresponding with The Guardian's Guide and HESA subject categories._ Unfortunately I could not find specific data surrounding LGBTQ+ demographics, so such data is absent from here. --- [HESA]: https://www.hesa.ac.uk/data-and-analysis/students [grauniad uni]: https://www.theguardian.com/education/ng-interactive/2019/jun/07/university-league-tables-2020 [Russell]: https://russellgroup.ac.uk/about/our-universities/ [Swan]: https://www.ecu.ac.uk/equality-charters/athena-swan/athena-swan-round-results/`34:T607,gSubStackedChart = { const svg = d3.create("svg").attr("viewBox", [0, 0, width, height]); if (chartType === 'stacked') { svg .append("g") .selectAll("g") .data(series) .join("g") .attr("fill", d => gSubColor(d.key)) .selectAll("rect") .data(d => d) .join("rect") .attr("x", (d, i) => gSubX(d.data.Subject)) .attr("y", d => gSubY(d[1])) .attr("height", d => gSubY(d[0]) - gSubY(d[1])) .attr("width", gSubX.bandwidth()) .append("title") .text( d => `${d.data.Subject} ${d.key} ${Math.round((100 * d.data[d.key]) / d.data['Total'])}%` ); } else { svg .append("g") .selectAll("g") .data(subjectCategoryData) .join("g") .attr("transform", d => `translate(${gSubX0(d.Subject)},0)`) .selectAll("rect") .data(d => subjectCategoryData.columns.map(key => ({ key, value: d[key], subject: d.Subject, percentage: Math.round((100 * d[key]) / d['Total']) })) ) .join("rect") .attr("x", d => gSubX1(d.key)) .attr("y", d => gSubY(d.value)) .attr("width", gSubX1.bandwidth()) .attr("height", d => gSubY(0) - gSubY(d.value)) .attr("fill", d => gSubColor(d.key)) .append('title') .text( d => `${d.subject} - ${d.key} ${d.percentage}%` ); } svg.append("g").call(gSubXAxis); svg.append("g").call(gSubYAxis); // svg.append("g").call(legend); return svg.node(); }35:T531,athenaSwan = ({ "Imperial College of Science, Technology and Medicine": { 9: 'bronze' }, "The University of Lancaster": { 0: 'bronze' }, "Loughborough University": { 9: 'bronze' }, "Newcastle University": { 0: 'silver' }, "University of Northumbria at Newcastle": { 0: 'bronze' }, "Queen Mary University of London": { 6: 'silver' }, "Queen's University Belfast": { 8: 'silver', 9: 'silver' }, "Swansea University": { 8: 'bronze' }, "University College London": { 8: 'silver', 7: 'bronze' }, "The University of Birmingham": { 9: 'bronze', 0: 'bronze' }, "The University of Central Lancashire": { 0: 'bronze' }, "The University of East Anglia": { 6: 'bronze', 8: 'bronze', 9: 'bronze' }, "The University of Exeter": { 7: 'bronze', 8: 'bronze' }, "University of Hertfordshire": { 8: 'bronze', 9: 'bronze' }, "The University of Liverpool": { 8: 'silver' }, "University of Nottingham": { 9: 'gold' }, "The University of Reading": { 0: 'silver' }, "The University of Sheffield": { 6: 'silver' }, "University of South Wales": { 0: 'bronze' }, "The University of Southampton": { 8: 'bronze' }, "The University of Warwick": { 8: 'bronze' } })36:T623,iChart = (x, y, z, aType = null, athena = false) => { const data = institutesTransformed .filter(institute => institute[y] > 0) .filter(institute => institute[x] > 0); const zoom = d3 .zoom() .scaleExtent([0.5, 32]) .on("zoom", zoomed); const svg = d3.create("svg").attr("viewBox", [0, 0, width, height]); const gGrid = svg.append("g"); const gDot = svg .append("g") .attr("fill", "none") .attr('stroke-width', 4) .attr("stroke-linecap", "round"); gDot .selectAll("path") .data(data) .join("path") .attr("d", d => `M${x1(d[x])},${y1(d[y])}h0`) .attr("stroke", d => (athena ? zAthena(d[z][aType]) : zRussell(d[z]))) .append('title') .text( d => `${d.heProvider} Rank - ${d[x]} Proportion - ${Math.round(d[y])}%` ); const gx = svg.append("g"); const gy = svg.append("g"); svg.call(zoom).call(zoom.transform, d3.zoomIdentity); svg.call; function zoomed() { const transform = d3.event.transform; const zx = transform.rescaleX(x1).interpolate(d3.interpolateRound); const zy = transform.rescaleY(y1).interpolate(d3.interpolateRound); gDot.attr("transform", transform).attr("stroke-width", 5 / transform.k); gx.call(iXAxis, zx); gy.call(iYAxis, zy); gGrid.call(iGrid, zx, zy); } // const gxl = svg.append('g').call(iXLabel); // const gyl = svg.append('g').call(iYLabel); return Object.assign(svg.node(), { reset() { svg .transition() .duration(750) .call(zoom.transform, d3.zoomIdentity); } }); }37:Tdfb,institutesTransformed = { const awardMap = { 0: 'overall', 6: 'physical', 7: 'maths', 8: 'cs', 9: 'engineering' }; const athenaRanks = ['none', 'bronze', 'silver', 'gold']; let it = institutes.map(institute => { let athenaAwarded = { ...defaultAthena }; let athenaInstitutes = Object.keys(athenaSwan); if (athenaInstitutes.indexOf(institute["HE provider"]) != -1) { for (const key in athenaSwan[institute["HE provider"]]) { athenaAwarded[awardMap[key]] = athenaSwan[institute["HE provider"]][key]; if ( athenaRanks.indexOf(athenaAwarded[awardMap[key]]) > athenaRanks.indexOf(athenaAwarded.best) ) { athenaAwarded.best = athenaAwarded[awardMap[key]]; } } } return { heProvider: institute["HE provider"], white: (100 * institute.White) / institute.Total_x, whiteCount: institute.White, black: (100 * institute.Black) / institute.Total_x, blackCount: institute.Black, asian: (100 * institute.Asian) / institute.Total_x, asianCount: institute.Asian, mixed: (100 * institute.Mixed) / institute.Total_x, mixedCount: institute.Mixed, otherRace: (100 * institute.Other_x) / institute.Total_x, otherRaceCount: parseInt(institute.Other_x), bame: (100 * (institute.Total_x - institute.White)) / institute.Total_x, bameCount: institute.Total_x - institute.White, unknownRace: (100 * institute['Not known']) / institute.Total_x, russellGroup: institute["Russell Group"] == 1, rankingOverall: institute['Guardian Ranking (Overall)'], rankingMechEng: institute['Guardian Ranking (MechEng)'], rankingMaths: institute['Guardian Ranking (Maths)'], rankingCs: institute['Guardian Ranking (CS)'], rankingElectricalEng: institute['Guardian Ranking (Electrical Eng)'], rankingAverage: institute['Average Ranking'], stateSchoolCount: parseInt( institute['Number from state schools or colleges'] ), stateSchoolPercentage: institute['Percentage from state schools or colleges'], stateSchoolBenchmark: institute['Benchmark (%)_x'], stateSchoolStandardDev: institute['Standard deviation (%)_x'], stateSchoolError: institute['+/-_x'], stateSchoolLocationBenchmark: institute['Location adjusted benchmark (%)_x'], stateSchoolLocationStandardDev: institute['Standard deviation (%).1_x'], stateSchoolLocationError: institute['+/-.1_x'], lowNeighbourhoodsCount: parseInt( institute['Number from low participation neighbourhoods'] ), lowNeighbourhoodPercentage: institute['Percentage from low participation neighbourhoods'], lowNeighbourhoodBenchmark: institute['Benchmark (%)_y'], lowNeighbourhoodStandardDev: institute['Standard deviation (%)_y'], lowNeighbourhoodError: institute['+/-_y'], lowNeighbourhoodLocationBenchmark: institute['Location adjusted benchmark (%)_y'], lowNeighbourhoodLocationStandardDev: institute['Standard deviation (%).1_y"'], lowNeighbourhoodLocationError: institute['+/-.1_y'], female: (100 * institute.Female) / institute.Total_y, femaleCount: institute.Female, male: (100 * institute.Male) / institute.Total_y, maleCount: institute.Male, otherGender: institute.Other_y / institute.Total_y, otherGenderCount: institute.Other_y, athena: athenaAwarded }; }); it['columns'] = Object.keys(it[0]); return it; }38:[{"id":"b49ce443b02c2358f7cc79af50bfbdec48f0365e071398b4d5a33cf8db9d36409b12a49955b17638888ed8985d28dc098ebfb6580adb25750b532393a9785eb8","href":"https://static.observableusercontent.com/files/b49ce443b02c2358f7cc79af50bfbdec48f0365e071398b4d5a33cf8db9d36409b12a49955b17638888ed8985d28dc098ebfb6580adb25750b532393a9785eb8","name":"mega_institutes@1.json","type":"application/json","lastModified":1596494577344.245,"size":101705},{"id":"ad733b7c3cdb6105c88eff6a53feb02e03957cbf88430b581d188cbfac996ce165e26877ec7a5546103a918fa69f62686713200f1ca0ab967e200c71d9fe9677","href":"https://static.observableusercontent.com/files/ad733b7c3cdb6105c88eff6a53feb02e03957cbf88430b581d188cbfac996ce165e26877ec7a5546103a918fa69f62686713200f1ca0ab967e200c71d9fe9677","name":"gender_subjects.json","type":"application/json","lastModified":1596486744064.823,"size":2169},{"id":"8d621f5b85ef79aee6a7559c8119b97536f9d81073b3ef10e9382ca867a8cb1ce860eaf471d30aa1b4a97f9158e848c902f3ed497ada5fa28fe2986ea8917e0b","href":"https://static.observableusercontent.com/files/8d621f5b85ef79aee6a7559c8119b97536f9d81073b3ef10e9382ca867a8cb1ce860eaf471d30aa1b4a97f9158e848c902f3ed497ada5fa28fe2986ea8917e0b","name":"ethnicity_subjects.json","type":"application/json","lastModified":1596647049986.259,"size":3041}] 31:{"id":"2038d5d328a97e30","slug":"dei-university","title":"DEI & University","thumbnail":"de0cbd10475a3a40ad168eb56c3d8015ed041d6b6806e34339190833bebafa46","access_level":"public","create_time":"$D2020-08-02T16:04:01.755Z","update_time":"$D2020-08-23T16:31:25.869Z","view_time":null,"first_public_time":"$D2020-08-06T11:28:27.026Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"85bbfb65264a0771","login":"mrkwse","name":"Mark Woosey","avatar_url":"https://avatars-next.observableusercontent.com/b9b2f5fcccef89a5835ba8e427c23e1a832ac39768f32279dded6e469ed03a31","tier":"starter_2024"},"version":946,"publish_version":946,"role":null,"authored":false,"authors":[{"type":"individual","id":"983e1527863eaf06","login":"mrkwse","name":"Mark 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category:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":516,"value":"viewof subjectCategory = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":898,"value":"md` Chart type:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":752,"value":"viewof chartType = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":864,"value":"viewof subjectSet = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":849,"value":"demoLegend = {\n const zDomain = gSubColor;\n const svg = d3.create(\"svg\").attr(\"viewBox\", [0, 0, width, 20]);\n\n const g = svg\n .attr(\"transform\", `translate(0,0)`)\n .attr(\"text-anchor\", \"end\")\n .attr(\"font-family\", \"sans-serif\")\n .attr(\"font-size\", 10)\n .selectAll(\"g\")\n .data(\n zDomain.domain().slice()\n // .reverse()\n )\n .join(\"g\")\n .attr(\"transform\", (d, i) => `translate(${i * 120},0)`);\n\n g.append(\"rect\")\n .attr(\"x\", 0)\n .attr(\"width\", 19)\n .attr(\"height\", 19)\n .attr(\"fill\", zDomain);\n\n g.append(\"text\")\n .attr(\"x\", 25)\n .attr(\"y\", 9.5)\n .attr(\"dy\", \"0.35em\")\n .attr('text-anchor', 'start')\n .text(d => d);\n\n return svg.node();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":104,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":801,"value":"md`## Demographic data by institute and institute's ranking according to Guardian Univeristy Guide\n\nThe following plot can be panned and zoomed and hovering over a point will show more specific information. \n\n**N.B.** The demographic data per institute (y-axis) is **not** specific to subject/department, but the total university admissions. This plot should be viewed in relation to/the context of the above chart, rather than in isolation.\n\nRanking category/subject (x-axis):`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":393,"value":"viewof scatterCategory = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":906,"value":"md`Demographic category (y-axis):`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":396,"value":"viewof category = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":909,"value":"md`University attribute (point colour):`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":573,"value":"viewof discriminant = html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":414,"value":"instituteLegend = {\n const zDomain = zKey[2] ? zAthena : zRussell;\n const svg = d3.create(\"svg\").attr(\"viewBox\", [0, 0, width, 20]);\n\n const g = svg\n .attr(\"transform\", `translate(0,0)`)\n .attr(\"text-anchor\", \"end\")\n .attr(\"font-family\", \"sans-serif\")\n .attr(\"font-size\", 10)\n .selectAll(\"g\")\n .data(\n zDomain\n .domain()\n .slice()\n .reverse()\n )\n .join(\"g\")\n .attr(\"transform\", (d, i) => `translate(${i * 120},0)`);\n\n g.append(\"rect\")\n .attr(\"x\", 0)\n .attr(\"width\", 19)\n .attr(\"height\", 19)\n .attr(\"fill\", zDomain);\n\n g.append(\"text\")\n .attr(\"x\", 25)\n .attr(\"y\", 9.5)\n .attr(\"dy\", \"0.35em\")\n .attr('text-anchor', 'start')\n .text(d => (zKey[2] ? d : `${d ? '' : 'Non-'}Russell Group`));\n\n return svg.node();\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":348,"value":"iChart(rank, category, zKey[0], zKey[1], zKey[2])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":806,"value":"md`---\n_Everything below here is code and data associated with the above visualisations._ It's a bit of a mess currently (I'd encourage use of the tree on the right hand side of the window)\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":117,"value":"legend = svg => {\n const g = svg\n .attr(\"transform\", `translate(${width - margin.right},0)`)\n .attr(\"text-anchor\", \"end\")\n .attr(\"font-family\", \"sans-serif\")\n .attr(\"font-size\", 10)\n .selectAll(\"g\")\n .data(\n gSubColor\n .domain()\n .slice()\n .reverse()\n )\n .join(\"g\")\n .attr(\"transform\", (d, i) => `translate(0,${i * 20})`);\n\n g.append(\"rect\")\n .attr(\"x\", -19)\n .attr(\"width\", 19)\n .attr(\"height\", 19)\n .attr(\"fill\", gSubColor);\n\n g.append(\"text\")\n .attr(\"x\", -24)\n .attr(\"y\", 9.5)\n .attr(\"dy\", \"0.35em\")\n .text(d => d);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":59,"value":"series = d3\n .stack()\n .keys(subjectCategoryData.columns.slice(1))(subjectCategoryData)\n .map(d => (d.forEach(v => (v.key = d.key)), d))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":82,"value":"gSubX = d3\n .scaleBand()\n .domain(genderSubjectsRelevant.map(d => d.Subject))\n .range([margin.left, width - margin.right])\n .padding(0.1)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":708,"value":"gSubX0 = d3\n .scaleBand()\n .domain(genderSubjectsRelevant.map(d => d.Subject))\n .rangeRound([margin.left, width - margin.right])\n .paddingInner(0.1)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":715,"value":"gSubX1 = d3\n .scaleBand()\n .domain(subjectCategoryData.columns)\n .rangeRound([0, gSubX0.bandwidth()])\n .padding(0.05)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":90,"value":"gSubY = d3\n .scaleLinear()\n .domain([0, d3.max(series, d => d3.max(d, d => d[1]))])\n .rangeRound([height - margin.bottom, margin.top])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":96,"value":"gSubColor = d3\n .scaleOrdinal()\n .domain(series.map(d => d.key))\n .range(d3.schemeAccent)\n .unknown(\"#ccc\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":98,"value":"gSubXAxis = g => g\n .attr(\"transform\", `translate(0,${height - 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height / 2)\n .attr(\"dy\", \"1em\")\n .style(\"text-anchor\", \"middle\")\n .text(category);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":833,"value":"iXLabel = g => {\n g.append(\"text\")\n .attr(\"y\", width / 2)\n .attr(\"x\", height)\n .style(\"text-anchor\", \"middle\")\n .text('Ranking');\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":302,"value":"k = height / width","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":180,"value":"institutesObject = FileAttachment(\"mega_institutes@1.json\").json();","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":208,"value":"institutes = {\n let ia = Object.values(institutesObject);\n ia['columns'] = Object.keys(ia[0]);\n return ia;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":243,"value":"institutes['columns']","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":579,"value":"defaultAthena = ({\n overall: 'none',\n physical: 'none',\n maths: 'none',\n cs: 'none',\n engineering: 'none',\n best: 'none'\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":606,"value":"defaultAthena","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":631,"value":"Object.keys(athenaSwan)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":633,"value":"institutes[47][\"HE provider\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":246,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":292,"value":"institutesTransformed['columns']","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":253,"value":"parseInt('100')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":17,"value":"d3 = require(\"d3@5\", \"d3-array@2\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W38","stdlib":"1","titling":"auto"}} 32:"$31:body"