31:Tbab,# Social reproduction in the French cinema: evidence from Wikidata In December 2022, the New York magazine did its cover story about the nepo-babies boom in Hollywood.Priyanka Mantha "On the Cover of New York Magazine: Extremely Overanalyzing Hollywood’s Nepo-Baby Boom", *New York Magazine*, December 19, 2022, https://nymag.com/press/2022/12/extremely-overanalyzing-hollywoods-nepo-baby-boom.html We have the same debates in France. French cinema is known for its dynasties and the place of the children of celebrities. This not new. 10 years ago, Le Monde had already published an article on the topic.Maxime Vaudano, "Césars : les "fils et filles de" bien représentés dans la "grande famille" du cinéma", *Le Monde*, February 22, 2013, https://www.lemonde.fr/culture/article/2013/02/22/cesars-les-fils-et-filles-de-bien-representes-dans-la-grande-famille-du-cinema_1837345_3246.html In a recent sketch, humorist Alex Vizorek suggests that there is now lots of children of celebrities in sport but "not as much as in French cinema".Alex Vizorek, Les "fils de" dans le sport - Vizo sport, *France Inter*, January 2023, https://www.youtube.com/watch?v=BttiZxTQzd8 As a data scientist, I like to dive into the data to test whether hunches are right or wrong.See [@pac02/actress-singers-and-actor-singers-do-actresses-become-sing]( https://observablehq.com/@pac02/actress-singers-and-actor-singers-do-actresses-become-sing) for a similar exploration. Wikidata provides a fantastic database to test the assumption that the number of children of celebrities is higher in the cinema than in other fields. I collect data about people of French citizenship (P27 is Q142) born after 1970 with a wikipedia article in Wikipedia in French (fr.wikipedia.org). For each occupation I collect the list of people and with the optional id of their father or mother if they have a wikipedia page. The most difficult part is to choose the good items for occupation. First I run a query to look at the main occupations of the population (https://qlever.cs.uni-freiburg.de/wikidata/NFgZ2y). So I choose to look at [actors (Q33999)](https://www.wikidata.org/wiki/Q33999), [musicians (Q639669)](https://www.wikidata.org/wiki/Q639669), [writers (Q36180)](https://www.wikidata.org/wiki/Q36180), [athletes (Q2066131)](https://www.wikidata.org/wiki/Q2066131), [politicians (Q82955)](https://www.wikidata.org/wiki/Q82955), [film directors (Q2526255)](https://www.wikidata.org/wiki/Q2526255). For each occupation, I compute the proportion of people whose father have a wikipedia article in fr.wikipedia.org, whose mother have a wikipedia article in fr.wikipedia.org, either the mother or the father or both. I use [qlever.cs.uni-freiburg.de](https://qlever.cs.uni-freiburg.de/wikidata/) instead of [query.wikidata.org](https://query.wikidata.org/) to avoid timeout errors.32:T701,get_people = ({ occupation = "Q33999", citizenship = "Q142", birthyear = 1970 }) => { const query = `PREFIX rdfs: PREFIX schema: PREFIX wd: PREFIX wdt: SELECT DISTINCT ?item ?itemLabel ?year ?father ?mother WHERE { ?item wdt:P31 wd:Q5; wdt:P106/wdt:P279* wd:${occupation}; wdt:P27 wd:${citizenship}; wdt:P569 ?birthdate; rdfs:label ?itemLabel FILTER(lang(?itemLabel) = "fr") . ?sitelink schema:about ?item; schema:isPartOf . FILTER(YEAR( ?birthdate ) >= ${birthyear} ) BIND(YEAR(?birthdate) AS ?year) OPTIONAL { ?item wdt:P22 ?father. ?fatherlink schema:about ?father; schema:isPartOf . } OPTIONAL { ?item wdt:P25 ?mother. ?motherlink schema:about ?mother; schema:isPartOf . } }`; return fetch( `https://qlever.cs.uni-freiburg.de/api/wikidata?query=${encodeURIComponent( query )}`, { headers: { accept: "application/sparql-results+json" } } ) .then((response) => response.json()) .then((res) => aq .from( res.results.bindings.map((d) => ({ item: d.item.value, itemLabel: d.itemLabel.value, year: d.year.value, father: d.father?.value, mother: d.mother?.value })) ) .derive({ daddy: (d) => 1 * (d.father !== undefined), mommy: (d) => 1 * (d.mother !== undefined), either: (d) => (d.father !== undefined) | (d.mother !== undefined), both: (d) => (d.father !== undefined) & (d.mother !== undefined) }) ); }33:[] 2f:{"title":"Social reproduction in the French cinema: evidence from Wikidata","cells":[{"id":0,"value":"$31","pinned":false,"hidden":false,"mode":"md"},{"id":308,"value":"## Results\n\n7,7% of French film directors born after 1970 have a father with a wikipedia article.","pinned":false,"hidden":false,"mode":"md"},{"id":276,"value":"Inputs.table(\n df\n .groupby(\"occupation\")\n .rollup({\n n: (d) => op.sum(d.daddy),\n total: (d) => op.count(),\n share: (d) => 100 * op.mean(d.daddy)\n })\n .orderby(aq.desc(\"share\")),\n {\n format: {\n share: sparkbar(\n d3.max(\n df.groupby(\"occupation\").rollup({\n share: (d) => 100 * op.mean(d.daddy)\n }),\n (d) => d.share\n )\n )\n }\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":310,"value":"3,4% of French actors born after 1970 have a mother with a wikipedia article.","pinned":false,"hidden":false,"mode":"md"},{"id":278,"value":"Inputs.table(\n df\n .groupby(\"occupation\")\n .rollup({\n n: (d) => op.sum(d.mommy),\n total: (d) => op.count(),\n share: (d) => 100 * op.mean(d.mommy)\n })\n .orderby(aq.desc(\"share\")),\n {\n format: {\n share: sparkbar(\n d3.max(\n df.groupby(\"occupation\").rollup({\n share: (d) => 100 * op.mean(d.mommy)\n }),\n (d) => d.share\n )\n )\n }\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":312,"value":"8,3% of French film directors born after 1970 have a father or a mother with a wikipedia article.","pinned":false,"hidden":false,"mode":"md"},{"id":286,"value":"Inputs.table(\n df\n .groupby(\"occupation\")\n .rollup({\n n: (d) => op.sum(d.either),\n total: (d) => op.count(),\n share: (d) => 100 * op.mean(d.either)\n })\n .orderby(aq.desc(\"share\")),\n {\n format: {\n share: sparkbar(\n d3.max(\n df.groupby(\"occupation\").rollup({\n share: (d) => 100 * op.mean(d.either)\n }),\n (d) => d.share\n )\n )\n }\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":318,"value":"2,9% of French film actors have a father and a mother with a wikipedia article.","pinned":false,"hidden":false,"mode":"md"},{"id":252,"value":"Inputs.table(\n df\n .groupby(\"occupation\")\n .rollup({\n n: (d) => op.sum(d.both),\n total: (d) => op.count(),\n share: (d) => 100 * op.mean(d.both)\n })\n .orderby(aq.desc(\"share\")),\n {\n format: {\n share: sparkbar(\n d3.max(\n df.groupby(\"occupation\").rollup({\n share: (d) => 100 * op.mean(d.both)\n }),\n (d) => d.share\n )\n )\n }\n }\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":367,"value":"## Conclusion\n\nLooking at the data in February 2023, I find much more children of famous people in the French cinema than in other occupations. My methodology only look at the probability that the parents have a wikipedia article. Of course the parents are not always in the cinema industry. It would be interesting to go further and look at the occupation of the parents. It would also be interesting to see if there is any gender difference in this pattern. The analysis could be easily replicated for any other country.","pinned":false,"hidden":false,"mode":"md"},{"id":387,"value":"## See also\n\n* [Probability of having notable parents by occupation and gender](https://observablehq.com/@pac02/notable-parents-by-occupation-and-gender)\n* [Probability of having notable parents by country of citizenship](https://observablehq.com/@pac02/probability-of-having-notable-parents-by-country-of-citize)","pinned":false,"hidden":false,"mode":"md"},{"id":197,"value":"## Appendix","pinned":false,"hidden":false,"mode":"md"},{"id":270,"value":"df\n .groupby(\"occupation\")\n .rollup({\n total: (d) => op.count(),\n daddy: (d) => op.mean(d.daddy),\n mommy: (d) => op.mean(d.mommy),\n either: (d) => op.mean(d.either),\n both: (d) => op.mean(d.both)\n })\n .view()","pinned":false,"hidden":false,"mode":"ojs"},{"id":205,"value":"actors = get_people({ occupation: \"Q33999\" }).then(d => d.derive({occupation: d => \"actors\"}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":211,"value":"musicians = get_people({ occupation: \"Q639669\" }).then(d => d.derive({occupation: d => \"musicians\"}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":220,"value":"writers = get_people({occupation: \"Q36180\"}).then(d => d.derive({occupation: d => \"writers\"}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":227,"value":"athletes = get_people({occupation: \"Q2066131\"}).then(d => d.derive({occupation: d => \"athletes\"}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":234,"value":"politicians = get_people({ occupation: \"Q82955\" }).then(d => d.derive({occupation: d => \"politicians\"}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":262,"value":"filmdirectors = get_people({occupation: \"Q2526255\"}).then(d => d.derive({occupation: d => \"film director\"}))","pinned":true,"hidden":false,"mode":"ojs"},{"id":216,"value":"df = actors\n .concat(musicians)\n .concat(writers)\n .concat(athletes)\n .concat(politicians)\n .concat(filmdirectors)","pinned":true,"hidden":false,"mode":"ojs"},{"id":141,"value":"$32","pinned":true,"hidden":false,"mode":"ojs"},{"id":324,"value":"// colors from https://colorhunt.co/palette/86a3b8e8d2a6f48484f55050\nfunction sparkbar(max) {\n return (x) => htl.html`

${x.toLocaleString(\"en\")}`;\n}","pinned":true,"hidden":false,"mode":"ojs"},{"id":382,"value":"I use the [arquero](https://uwdata.github.io/arquero/api/) library which provides a very intuitive way to handle tabular data inspired by R's [dplyr](https://dplyr.tidyverse.org/) library. ","pinned":false,"hidden":false,"mode":"md"},{"id":110,"value":"import { aq, op } from \"@uwdata/arquero\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":380,"value":"I use [Aaron's Stylesheet for Observable](https://observablehq.com/@ajar/css) which is a nice stylesheet inspired by [Tufte.css](https://edwardtufte.github.io/tufte-css/). It provides nice side notes.","pinned":false,"hidden":false,"mode":"md"},{"id":349,"value":"import { stylesheet } from \"@ajar/css\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":363,"value":"stylesheet","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}