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Why do gender gaps in education and work persist

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Despite significant progress in narrowing or closing some long-standing gender gaps in many areas of education and employment, in most countries, boys and girls are still not likely to be equally proficient in academic subjects, such as reading, mathematics and science. Moreover, boys and girls still show markedly different attitudes towards learning and aspirations for their future – and that has a significant impact on their decisions to pursue further education and on their choice of career.

This webinar presents OECD data highlighting how differences in attitudes towards failure and competition among boys and girls can influence their decisions about what to study in school and their career expectations. The data also illustrate how these attitudes, developed early in life, influence men’s and women’s career choices later on.

Published in: Education
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Why do gender gaps in education and work persist

  1. 1. Why do gender gaps in education and work persist? Andreas Schleicher
  2. 2.  Gender gaps in educational attainment pretty much closed in developed countries  Persistent gaps in labour market outcomes mostly tracked to differences in attitudes towards learning and aspirations for future during secondary school.  These attitudes, developed early in life, affect college major / occupational segregation, in turn affecting labour market outcomes.  Differences in STEM-readiness at college entry traced back to high school choices Motivation
  3. 3. How girls and boys are performing in schools ….
  4. 4. 0 10 20 30 40 50 60 70 Peru Colombia Mexico B-S-J-Z(China) Panama CostaRica Argentina UnitedKingdom Chile Japan Belgium ChineseTaipei Macao(China) Belarus Uruguay Singapore Ireland Korea UnitedStates Portugal France Russia Indonesia Italy Kosovo Turkey Baku(Azerbaijan) Brazil Germany Morocco Malaysia Hungary Kazakhstan Philippines Lebanon Austria NewZealand Netherlands Canada Luxembourg Denmark OECDaverage BosniaandHerzegovina BruneiDarussalam Montenegro Switzerland Estonia DominicanRepublic Australia Poland Latvia Croatia CzechRepublic Ukraine Romania Sweden SlovakRepublic HongKong(China) Serbia Albania Georgia Lithuania Thailand Moldova Bulgaria Iceland Slovenia Greece Norway Israel Malta Jordan Finland NorthMacedonia SaudiArabia UnitedArabEmirates Qatar Score-pointdifference(girls-boys) Girls perform better in reading than boys in all countries/economies All differences are statistically significant Girls perform better in reading than boys in all countries/economies Fig II.7.1
  5. 5. -20 -10 0 10 20 30 40 Peru Colombia B-S-J-Z(China) Argentina CostaRica Mexico Hungary Portugal* Belgium Korea Singapore Chile Uruguay Italy Belarus Japan UnitedKingdom Spain Austria Ukraine NewZealand Australia ChineseTaipei UnitedStates* Panama Poland Switzerland Romania Russia BosniaandHerzegovina France Germany Ireland Brazil CzechRepublic Macao(China) Denmark OECDaverage Canada Philippines Croatia Montenegro Luxembourg Lebanon Estonia Serbia Baku(Azerbaijan) Kosovo SlovakRepublic Lithuania Malaysia Indonesia BruneiDarussalam Kazakhstan Turkey Sweden Netherlands* Latvia Iceland HongKong(China)* Morocco DominicanRepublic Slovenia Norway Moldova Greece Georgia Bulgaria Albania NorthMacedonia Israel Thailand Malta Cyprus Finland UnitedArabEmirates SaudiArabia Jordan Qatar Score-pointdifference(girls-boys) … and also score similar or higher than boys in science in most countries All differences are statistically significant Fig II.7.5
  6. 6. and do not score much lower than boys in mathematics either… -25 -20 -15 -10 -5 0 5 10 15 20 25 30 Colombia391 CostaRica402 Peru400 Italy487 Argentina379 Austria499 UnitedKingdom502 Belgium508 Mexico409 B-S-J-Z(China)591 Japan527 Portugal492 NewZealand494 Hungary481 Croatia464 UnitedStates478 Brazil384 Estonia523 Uruguay418 Montenegro430 Panama353 Baku(Azerbaijan)420 Luxembourg483 Chile417 Switzerland515 Germany500 Ukraine453 Latvia496 Spain481 France495 Belarus472 Australia491 Ireland500 Romania430 OECDaverage489 Turkey454 Canada512 Russia488 SlovakRepublic486 Kosovo366 Singapore569 Korea526 Denmark509 Macao(China)558 ChineseTaipei531 CzechRepublic499 Serbia448 BosniaandHerzegovina406 Poland516 Netherlands519 Kazakhstan423 Morocco368 Slovenia509 Greece451 Lebanon393 Sweden502 Bulgaria436 Moldova421 Lithuania481 DominicanRepublic325 Georgia398 Albania437 HongKong(China)551 Finland507 Jordan400 Malaysia440 Norway501 NorthMacedonia394 BruneiDarussalam430 UnitedArabEmirates435 Israel463 Indonesia379 Iceland495 Philippines353 Malta472 SaudiArabia373 Thailand419 Qatar414 Score-pointdifference(girlsminusboys)
  7. 7. [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] 330 350 370 390 410 430 450 470 490 510 530 550 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 Meansocreinreading Gender gap in reading performance OECD average: 487 points OECDaverage:30 Above-average performance Above-average gender gap Below-average performance Above-average gender gap Above-average performance Below-average gender gap Below-average performance Below-average gender gap Larger gender gap in favour of girls Higherperformance READING PERFORMANCE
  8. 8. 0 5 10 15 20 25 30 35 40 45 50 Singapore B-S-J-Z(China) Germany UnitedStates NewZealand Australia Korea Sweden Canada Ireland UnitedKingdom Finland ChineseTaipei Israel Macao(China) Belgium Poland HongKong(China) Estonia France Japan Netherlands Switzerland CzechRepublic OECDaverage Luxembourg Austria Portugal Norway Denmark Slovenia Iceland Hungary Malta SlovakRepublic Italy UnitedArabEmirates Lithuania Russia Belarus Turkey Croatia Latvia Chile Greece Ukraine Qatar Brazil Bulgaria Serbia Uruguay BruneiDarussalam Romania Colombia Mexico CostaRica Argentina Lebanon Montenegro Moldova Kazakhstan BosniaandHerzegovina NorthMacedonia Jordan Baku(Azerbaijan) % Percentage of top performers in reading Girls in the bottom quarter of ESCS Boys in the bottom quarter of ESCS Girls in the top quarter of ESCS Boys in the top quarter of ESCS Among top performers in reading, girls perform markedly better than boys among advantaged socio-economic groups
  9. 9. 0 10 20 30 40 50 60 70 B-S-J-Z(China) Macao(China) HongKong(China) Singapore Korea ChineseTaipei Canada Japan Netherlands Slovenia Estonia Switzerland UnitedKingdom Iceland Poland NewZealand Sweden Germany Norway Belgium Denmark Australia Finland OECDaverage CzechRepublic Russia Portugal Malta Ireland Luxembourg SlovakRepublic Austria Italy Lithuania Spain France Latvia Israel UnitedStates Croatia Serbia Turkey Ukraine Belarus Hungary Greece Kazakhstan BruneiDarussalam Albania UnitedArabEmirates Thailand Lebanon Montenegro Bulgaria Qatar Baku(Azerbaijan) Malaysia Chile NorthMacedonia Romania Moldova Uruguay Colombia Jordan BosniaandHerzegovina Brazil Georgia Morocco Indonesia Kosovo CostaRica Argentina Mexico Peru % Percentage of top performers in mathematics Girls in the bottom quarter of ESCS Boys in the bottom quarter of ESCS Girls in the top quarter of ESCS Boys in the top quarter of ESCS But among top performers in mathematics, boys perform markedly better among advantaged socio-economic groups Fig II.7.8 Statistically significant differences between girls and boys in the top and/or bottom quarters of socio-economic status are marked in a darker tone Top performers are students who performed at or above Level 5
  10. 10. Hidden challenges for girls and boys… …. and what education could do for gender equality
  11. 11. -1.00 -0.50 0.00 0.50 1.00 1.50 B-S-J-Z(China) Turkey Albania Kosovo Philippines Georgia Kazakhstan Peru Baku(Azerbaijan) UnitedArabEmirates Jordan DominicanRepublic Brazil Malaysia VietNam Russia Mexico Indonesia Colombia Moldova Belarus Bulgaria SaudiArabia Uruguay BruneiDarussalam Ukraine Poland Panama Italy Morocco ChineseTaipei SlovakRepublic Romania Qatar Singapore Montenegro Spain Portugal HongKong(China) Hungary CostaRica Macao(China) Japan Greece Thailand CzechRepublic Chile Estonia Canada Korea Latvia Malta Israel Serbia BosniaandHerzegovina Argentina OECDaverage Lithuania Ireland UnitedStates NewZealand France Germany Australia Slovenia Austria Finland Luxembourg Switzerland UnitedKingdom Croatia Iceland Sweden Denmark Belgium Norway Netherlands Girls Boys Indexofenjoymentofreading In all countries/economies girls enjoy reading more than boys All differences between girls and boys are statistically significant
  12. 12. 0 10 20 30 40 50 60 70 80 Reading is one of my favourite hobbies Participating in social networks Chatting on line Playing online games via social networks Playing one-player games Playing collaborative online games Percentage of students engaging in the following activities every day or almost every day Girls Boys% ..and they differ from boys in their engagement in ICT activities All differences between girls and boys are statistically significant OECD average Categories related on ITC use was based on optional ICT familiarity questionnaire distributed in 31 OECD participating countries Most boys engage more in gaming activities than girls
  13. 13. These differences in the activities students engage highlight that…
  14. 14. -0.50 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 CostaRica NorthMacedonia Italy UnitedArabEmirates Jordan Malaysia Slovenia Kosovo Morocco Panama Mexico Peru Qatar Israel Thailand Malta Argentina Chile Greece Korea SaudiArabia Indonesia Brazil Uruguay Singapore Spain B-S-J-Z(China) Croatia Georgia UnitedStates BruneiDarussalam Bulgaria DominicanRepublic ChineseTaipei BosniaandHerzegovina Poland Colombia Canada Philippines Turkey Serbia Portugal Baku(Azerbaijan) Kazakhstan Lebanon Norway Macao(China) OECDaverage Romania Australia NewZealand Lithuania Moldova Ukraine Hungary Austria Denmark HongKong(China) Latvia Montenegro Germany Ireland Japan Iceland Belarus UnitedKingdom Switzerland SlovakRepublic France Luxembourg CzechRepublic Finland Estonia Sweden Russia Netherlands Indexofmotivationtomastertasks Girls Boys Girls are more motivated to master tasks than boys Statistically significant gender differences are shown in a darker tone Fig II.8.4
  15. 15. -0.50 -0.40 -0.30 -0.20 -0.10 0.00 0.10 0.20 0.30 0.40 0.50 0.60 Jordan UnitedArabEmirates Malaysia SaudiArabia NorthMacedonia B-S-J-Z(China) Qatar Morocco BruneiDarussalam Turkey ChineseTaipei Lebanon Romania Baku(Azerbaijan) Peru CostaRica Malta Singapore Kosovo Indonesia HongKong(China) Macao(China) Georgia Israel Moldova Panama UnitedStates Mexico Colombia Philippines Italy Canada Thailand Lithuania DominicanRepublic Ireland Chile NewZealand Australia UnitedKingdom Bulgaria Hungary Denmark Belarus Norway Latvia BosniaandHerzegovina Korea Montenegro Russia OECDaverage Spain Greece Poland Finland Iceland Japan SlovakRepublic Austria Brazil Estonia Germany CzechRepublic Sweden Netherlands Croatia Argentina Portugal Luxembourg Slovenia Uruguay Kazakhstan Ukraine France Belgium Switzerland Serbia Indexofattitudestowardscompetition Girls Boys BUT boys have stronger attitudes towards competition than girls in most of the countries Statistically significant gender differences are shown in a darker tone Fig II.8.3
  16. 16. -0.7 -0.6 -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 ChineseTaipei Singapore Macao(China) BruneiDarussalam UnitedKingdom HongKong(China) Canada Japan NewZealand Australia Ireland Malaysia Malta UnitedStates Korea Iceland France Sweden Denmark Slovenia Philippines Italy Thailand Poland Turkey Portugal OECDaverage Chile Brazil SlovakRepublic CzechRepublic Lithuania Hungary UnitedArabEmirates Moldova Baku(Azerbaijan) Latvia Mexico B-S-J-Z(China) Luxembourg Finland Greece VietNam Estonia Belarus DominicanRepublic Spain Belgium(Flemish) Argentina Kosovo Uruguay Bulgaria Qatar Russia NorthMacedonia Morocco Panama Croatia Ukraine Switzerland Austria Colombia Romania CostaRica Indonesia Netherlands Germany Peru Lebanon Jordan Albania Serbia Kazakhstan Georgia BosniaandHerzegovina Montenegro SaudiArabia Indexoffearoffailure Girls Boys AND are less afraid of failure than girls Statistically significant gender differences are shown in a darker tone Fig II.8.6 Girls are more afraid of failure than boys in all countries/economies except in Saudi Arabia.
  17. 17. What impact might these attitudes developed early in life have? Differences in career expectations Differences in field of study choices Differences in labour market outcomes
  18. 18. Boys Girls 1st Police officers Specialist medical practitioners 2nd Athletes and sports players Generalist medical practitioners 3rd Engineering professionals Lawyers 4th Generalist medical practitioners Teaching professionals 5th Business services and administration managers Nursing professionals 6th Motor vehicle mechanics and repairers Medical doctors 7th Armed forces occupations, other ranks Psychologists 8th Policy and planning managers Police officers 9th Lawyers Veterinarians 10th Teaching professionals Policy and planning managers Career expectations among girls and boys are already different at 15 year-old Tab II.6.1 Top 10 career expectations of 15-year-old boys and girls
  19. 19. 0 5 10 15 20 25 30 35 40 45 50 Argentina Lebanon Greece Albania Chile Qatar Turkey Sweden Brazil UnitedKingdom NorthMacedonia Australia BruneiDarussalam Montenegro Serbia France Denmark Ireland Hungary Croatia Belgium UnitedArabEmirates Israel Estonia Portugal Malaysia Malta Luxembourg Slovenia Thailand NewZealand OECDaverage-36 Kazakhstan Iceland Canada Lithuania Baku(Azerbaijan) Italy Germany Russia Latvia Singapore Poland Norway Bulgaria Romania Switzerland Jordan Moldova Belarus SlovakRepublic UnitedStates B-S-J-Z(China) Finland Austria ChineseTaipei Netherlands CzechRepublic Macao(China) Korea HongKong(China) Ukraine Indonesia Japan Percentageoftopperformerswhoexpectacareerinthefield Science and engineering professionals Top performers among all students Girls Boys Amongst top performers in mathematics and/or science, more boys than girls expect to take up a career in science and engineering Statistically significant differences are shown in a darker tone Fig II.8.8 "top performers" refers to students who attain at least Level 2 in all three core subjects and Level 5 or 6 in mathematics and/or science
  20. 20. 0 5 10 15 20 25 30 35 40 45 50 Jordan Turkey Portugal Chile Thailand Lebanon Brazil Canada Malaysia SlovakRepublic UnitedStates Qatar Finland NewZealand Albania Romania Australia Uruguay Indonesia Iceland Croatia Lithuania Slovenia Malta Poland Ireland Singapore OECDaverage-36 Denmark BruneiDarussalam Netherlands CzechRepublic Greece Baku(Azerbaijan) France Switzerland Norway Israel Macao(China) Belarus Luxembourg Belgium Japan Latvia Austria ChineseTaipei HongKong(China) Germany Hungary Bulgaria Italy Sweden Serbia Estonia Moldova UnitedKingdom Argentina Montenegro Kazakhstan Russia Korea Ukraine NorthMacedonia B-S-J-Z(China) Percentageoftopperformerswhoexpectacareerinthefield Health-related occupations Top performers among all students Girls Boys …while most top-performing girls expect to take up health-related professions Statistically significant differences are shown in a darker tone "top performers" refers to students who attain at least Level 2 in all three core subjects and Level 5 or 6 in mathematics and/or science
  21. 21. 0 5 10 15 20 25 30 Engineering, manufacturing and construction Business, administration and law Arts and humanities, social sciences, journalism and information Information and communication technologies Health and welfare Education Natural sciences, mathematics and statistics (%) 25-64 year-old adults (2018) Graduates (2017) 0 5 10 15 20 25 30 Business, administration and law Arts and humanities, social sciences, journalism and information Health and welfare Education Engineering, manufacturing and construction Natural sciences, mathematics and statistics Information and communication technologies (%) 25-64 year-old adults (2018) Graduates (2017) ..but field of study choices at the tertiary level mirror career expectations from school Distribution of male recent graduates and tertiary-educated 25-64 year-olds Distribution of female recent graduates and tertiary-educated 25-64 year-olds
  22. 22. How are labour market outcomes affected? - Skills for men and women evolve differently over time - Gender wage gap
  23. 23. Girls’ advantage in reading proficiency disappears by early adulthood…. …. while boys’ advantage in mathematics proficiency increases steadily, in an almost linear fashion -50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 50% Age 9-10 Age 15-16 Age 26-27 %ofastandarddeviation Literacy Numeracy Evolution of the gender gap in literacy and numeracy over time
  24. 24. Evolution of the gender gap in numeracy by country -50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 50% %ofastandarddeviation Age 9-10 Age 15-16 Age 26-27
  25. 25. Evolution of the gender gap in literacy by country -50% -40% -30% -20% -10% 0% 10% 20% 30% 40% 50% Czech Rep. France Germany Italy Netherlands Norway Russian Federation Sweden England United States %ofastandarddeviation Age 9-10 Age 15-16 Age 26-27
  26. 26. Women also tend to receive lower relative net financial returns on investing in tertiary education than men 0 100 000 200 000 300 000 400 000 500 000 600 000 700 000 Man Woman In equivalent USD converted using PPPs
  27. 27. On average, with a degree in the same field of study, women’s earnings in the workplace still lag behind men’s 50 60 70 80 90 100 110 All tertiary Education Business, administration and law ICT % Women earn more than men Women earn less than men
  28. 28. Seemingly innocuous factors, like differences in adolescents’ attitudes towards failure and competition, and their career expectations… …translate into differences in choices of fields of study and professions …which, in turn, influence earnings and other labour market outcomes like skills evolution over time. In sum..
  29. 29. Early interventions that promote girls’ self-confidence and willingness to compete could help narrow gender gaps in school and later on in life. As well as promoting understanding among Teachers and Employers on differences in gender attitudes and self- promotion
  30. 30. www.oecd.org/pisa www.oecd.org/skills/piaac www.oecd.org/education/education-at-a-glance www.oecd.org/gender Andreas.SCHLEICHER@oecd.org Marta.ENCINAS-MARTIN@oecd.org For more information
  31. 31. EXTRA SLIDES
  32. 32. 0 0 0 1 1 1 1 1 2 2 2 0 200 400 600 800 1000 Score points Reading Distribution of proficiency in reading and mathematics, by gender Largershareofstudents Girls Boys 0 200 400 600 800 1000 Score points Mathematics All PISA countries and economies average This figure is a histogram of performance using an interval size of five score points. ! Fig II.7.4
  33. 33. 0 10 20 30 40 50 60 70 80 90 100 Philippines DominicanRepublic Lebanon Kosovo Morocco Panama Indonesia Peru Georgia Argentina Kazakhstan Colombia Thailand Baku(Azerbaijan) BruneiDarussalam Bulgaria Brazil BosniaandHerzegovina Mexico NorthMacedonia Albania Uruguay Malaysia Qatar SaudiArabia Moldova Romania CostaRica UnitedArabEmirates Montenegro SlovakRepublic Israel Jordan Serbia Malta Hungary Chile Luxembourg Belarus Greece Ukraine Belgium Switzerland CzechRepublic Austria Italy Portugal Lithuania Turkey France OECDaverage Iceland Netherlands Germany Russia Sweden NewZealand UnitedStates Latvia Australia ChineseTaipei Croatia UnitedKingdom Japan Denmark Norway Korea Slovenia Ireland Poland Canada Singapore Finland Estonia HongKong(China) Macao(China) B-S-J-Z(China) % Percentage of low achievers in reading Girls in the bottom quarter of ESCS Boys in the bottom quarter of ESCS Girls in the top quarter of ESCS Boys in the top quarter of ESCS Distribution of low achievers in reading, by gender and socio-economic status Fig II.7.6 Statistically significant differences between girls and boys in the top and/or bottom quarters of socio-economic status are marked in a darker tone Low achievers are students who performed below Level 2
  34. 34. [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] 0 10 20 30 40 50 60 70 -0.10 0.00 0.10 0.20 0.30 0.40 0.50 Gendergapinreadingperformance(girls-boys) Gender gap in index of perceived competence in reading (girls - boys) OECD average: 30 Score Points OECDaverage: 0.142 Gender gap in reading performance and perceived competence in reading Girls have higher perceived competence in reading than boys Girlsoutperformedboysinreading Below-average gender gap in reading performance Above-average gender gap in the Index of perceived competence Above-average gender gap in reading performance AND in the Index of perceived competence Below-average gender gap in reading performance AND in the Index of perceived competence Above-average gender gap in reading performance Below-average gender gap in the Index of perceived competence Fig II.8.5
  35. 35. [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE][CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] [CELLRANGE] 330 350 370 390 410 430 450 470 490 510 530 550 0510152025 Readingperformance(inscorepoints) Percentage of variation in performance explained by social-economic status Reading performance and equity 2018 Greater equity HigherPerformance Low performance Low equity High performance High equity Some countries combine equity and excellence

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