2b:null 2c:["$","title",null,{"children":"Gender-o-meter: Women do better in 10.000 meters | Jaume | Observable"}] 31:Tc65,graph10000m = { var woman = { x: [1966, 1966, 1967, 1970, 1971, 1975, 1975, 1977, 1977, 1978, 1981, 1981, 1982, 1983, 1983, 1984, 1985, 1986, 1993, 2016, 2021, 2021], y: [39.42, 39.17, 38.11, 35.51, 34.85, 35.01, 34.02, 33.57, 33.25, 32.72, 32.51, 32.28, 31.59, 31.58, 31.46, 31.22, 30.99, 30.23, 29.53, 29.29, 29.11, 29.01], fill: 'tozeroy', type: 'scatter', fillcolor: 'rgba(255, 190, 200, 0.5)', hovermode: 'closest', dragmode: 'select', selectdirection: 'h', name: 'Women' }; var man = { x: [1911, 1921, 1924, 1924, 1924, 1937, 1938, 1939, 1944, 1949, 1949, 1949, 1950, 1953, 1954, 1956, 1956, 1960, 1962, 1963, 1965, 1972, 1973, 1977, 1978, 1984, 1989, 1993, 1993, 1994, 1995, 1996, 1997, 1997, 1998, 2004, 2005, 2020], y: [30.98, 30.67, 30.59, 30.38, 30.10, 30.09, 30.03, 29.87, 29.59, 29.47, 29.45, 29.35, 29.04, 29.02, 28.90, 28.71, 28.50, 28.31, 28.30, 28.26, 27.66, 27.63, 27.51, 27.50, 27.37, 27.23, 27.13, 27.13, 26.97, 26.87, 26.72, 26.63, 26.52, 26.46, 26.37, 26.33, 26.29, 26.18], fill: 'tonexty', type: 'scatter', fillcolor: 'rgba(0, 50, 200, 0.5)', hovermode: 'closest', name: 'Men' }; var data = [ man,woman]; var annotations=[{x:2021, y:29.01, xref:'x', yref:'y', text:'Letesenbet Gidey
29.01 World Record', ax:40, ay:-40}, {x:1986, y:33, xref:'x', yref:'y', text:'Women progression: 9m 36s lowered
in 55 years of WRs
', ax:40, ay:-40}, {x:1953, y:29.01, xref:'x', yref:'y', text:'Emil Zátopek
WR in 1953', ax:40, ay:-40}, {x:1933, y:32, xref:'x', yref:'y', text:'Men progression: 3m 47s lowered
in 109 years of WRs
', ax:40, ay:-40}] const div = DOM.element('div'); Plotly.newPlot(div, data, { width: width, title : "10.000 meters World Records", annotations:annotations, xaxis: { title: { text: 'Years' }, range: [1910,2022], spikemode: "across" }, yaxis: { title: { text: 'Time(minutes)', }, range: [25,40], spikemode: "across" } , updatemenus: [ { x: 0, y: 0, yanchor: 'top', xanchor: 'left', showactive: false, direction: 'left', type: 'buttons', pad: { t: 87, r: 10 }, buttons: [ { method: 'update', args: [ {'visible': [true]}, { 'annotations': annotations } ], label: 'Show Anotacions' },{ method: 'update', args: [ {'visible': [true,true, false, false, false, false, false]}, { 'annotations': null } ], label: 'Hide Anotacions' }] }] }, ); return div; }32:[{"id":"cb2b35193cb6dd8092cbd94d7ea00a4048e19c10001aaf287a7765222cbe5cc0391eb753eeda170156463b5f4765c30e0ed37761709527571a853870aa93c260","href":"https://static.observableusercontent.com/files/cb2b35193cb6dd8092cbd94d7ea00a4048e19c10001aaf287a7765222cbe5cc0391eb753eeda170156463b5f4765c30e0ed37761709527571a853870aa93c260","name":"100m-Men@1.csv","type":"text/csv","lastModified":1627294972587.055,"size":239},{"id":"d548d3e9f760d47d9fd75bfa148b21ae34f6d4df87fe01589f742d550542f5a19f95089314463c7bb1a2599c1406d0c9136e4e5c14a9758684a8d3f0c9bbd3ca","href":"https://static.observableusercontent.com/files/d548d3e9f760d47d9fd75bfa148b21ae34f6d4df87fe01589f742d550542f5a19f95089314463c7bb1a2599c1406d0c9136e4e5c14a9758684a8d3f0c9bbd3ca","name":"100m-Women.csv","type":"text/csv","lastModified":1627294972587.055,"size":520}] 2f:{"id":"5b59062047fb6b96","slug":"gender-o-meter-10000m","title":"Gender-o-meter: Women do better in 10.000 meters","thumbnail":"d6f0d0905ca7705acba9555cde5c647609ebeb86b16026c326fae59338d2a735","access_level":"public","create_time":"$D2021-07-26T10:22:52.587Z","update_time":"$D2022-09-17T22:49:25.469Z","view_time":null,"first_public_time":"$D2021-07-26T15:10:55.583Z","fork":{"id":"caffbc00e1907c88","slug":"gender-o-meter-marathon","title":"Gender-o-meter: Women do better in Marathon","owner":{"id":"56e50593bfe6266e","login":"jaumet","name":"Jaume"}},"stars":0,"starred":false,"owner":{"type":"team","id":"56e50593bfe6266e","login":"jaumet","name":"Jaume","avatar_url":"https://avatars-next.observableusercontent.com/b2c7fe70708b1da9ab2a7f2eeff7c50402c89318b40ebc73624b52603217be30","tier":"starter_2024"},"version":598,"publish_version":598,"role":null,"authored":false,"authors":[{"type":"individual","id":"eed166f4705e97b7","login":"jaumet","name":"Jaume","avatar_url":"https://avatars-next.observableusercontent.com/b2c7fe70708b1da9ab2a7f2eeff7c50402c89318b40ebc73624b52603217be30","tier":null}],"members":[{"type":"individual","id":"eed166f4705e97b7","login":"jaumet","name":"Jaume","avatar_url":"https://avatars-next.observableusercontent.com/b2c7fe70708b1da9ab2a7f2eeff7c50402c89318b40ebc73624b52603217be30","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"subscribed":null,"forks":0,"collection":{"id":"54e65e5e1b3ecc76","slug":"gender-o-meter","title":"Gender-o-meter","owner":{"id":"56e50593bfe6266e","login":"jaumet","name":"Jaume"}},"type":"notebook","body":{"title":"Gender-o-meter: Women do better in 10.000 meters","cells":[{"id":393,"value":"md`# Gender-o-meter: Women do better in 10.000 meters`\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":20,"value":"md`Women are silenced in most of the fields in life. In sports is not different. Let's take a look back and check how \"ladies\" are doing in sport. Gender-o-meter is based on facts, this is athletes, dates and World Records, and its progression and comparison between Women and Men in several Olympic categories. \nIs it for you a surprise to affirm that women do quite a lot better than men?\n\nLet's start: Ready. Steady. Go!\n`\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":399,"value":"navbar = md`\n# Browse disciplines:\n\n## > Athletics: [100m](https://observablehq.com/@jaumet/gender-o-meter-100m) | [1500m](https://observablehq.com/@jaumet/gender-o-meter-1500m) | [10.000m](https://observablehq.com/@jaumet/gender-o-meter-10000m) | [Marathon](https://observablehq.com/@jaumet/gender-o-meter-marathon) | [High Jump](https://observablehq.com/@jaumet/gender-o-meter-highjump) | [Triple Jump](https://observablehq.com/@jaumet/gender-o-meter-triple-jump)\n\n## > Swimming: [200m freestyle](https://observablehq.com/@jaumet/gender-o-meter-200mfreestyle)\n--------\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":383,"value":"md `\n## > 10.000 meters World Records \n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":215,"value":"progression = html `\n\n

1. Comparison

-> Check these two videos: Letesenbet Gidey (ETH) runs in 2021 at the same speed as Emil Zátopek (CZE) in 1953.

-> Letesenbet Gidey (ETH), 29:01.03 WR, runs faster than any other man before Emil Zátopek (CZE) 29:01.6 WP in 1963.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":125,"value":"html` \n
\n
\n
Letesenbet Gidey 10.000 meters WR's in June 8th 2021 with a time of 29:01.4 - Hengelo, Netherlands
\n\n
\n
A video of Emil Zátopek (CZE) I found called \"Selected Originals - Pirie: Athlete Of The Year Aka Zatepek (1953)\".
\n
\n
`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":557,"value":"html `\n
2. Women's World Records Progression is Higher than Men's
\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
Women Men
In 55 yeas (*) In 109 years ()
9m 36s lowered 3m 47s lowered
This is 17m 27s in 100 years This is 3m 28s in 100 years
\n
-> Women's WR registration started 55 years after Men.
\n
-> Women advance about 20% faster than men in 10.000 meters' WP
\n
-> Women's 10.000 meters WR progression is 5 times faster than Men!**
\n
(*): WR counted since 1966
\n
(**): WR counted since 1911
\n

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":237,"value":"html `\n
3. History
\n
Below we present the diagrams of the WR evolution for Women and Men.
\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":112,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":266,"value":"credits = html `\n
Credits and resources
\n\n
> An idea and development of Jaume Nualart @jaumetet with the invaluable collaboration of Mar Canet @mcanet
\n
> The data is all from wikipedia: women WR, men WR, etc.
\n
> Made in Observableshp with Plotly
\n\n
\n\n\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":291,"value":"Plotly = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":444,"value":"import {SummaryTable} from \"@observablehq/summary-table\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":468,"value":"women = FileAttachment(\"100m-Women.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":472,"value":"men = FileAttachment(\"100m-Men@1.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W32","stdlib":"1","titling":"auto"}} 30:"$2f:body"

Women	Men
In 55 yeas (*)	In 109 years (**)
9m 36s lowered	3m 47s lowered
This is 17m 27s in 100 years	This is 3m 28s in 100 years