Resumen del artículo Gender, achievement, and subject choice in English education

publicado en Oxford Review of Economic Policy, Volume 36, Number 4, 2020, pp. 816–835

Inglaterra
género
logros
elección carreras
Autor/a

Virginia Robano

Fecha de publicación

10 de julio de 2024

Fecha de modificación

23 de septiembre de 2024

Resumen

La brecha de género en la educación inglesa afecta tanto los logros académicos como la elección de asignaturas, especialmente en áreas STEM. Las niñas superan a los niños en lectura y escritura desde las primeras etapas educativas, pero esta ventaja no se traduce en matemáticas y ciencias, donde ambos géneros presentan rendimientos similares. Además, las niñas tienden a evitar asignaturas STEM en la secundaria, influenciadas por estereotipos de género y la falta de modelos a seguir femeninos. Para cerrar esta brecha y fomentar una sociedad más equitativa hay que implementar políticas que promuevan la participación femenina en STEM desde una edad temprana y contrarrestar los sesgos implícitos en el entorno educativo.

Logros Académicos y Elección de Asignaturas en la Educación Inglesa: Perspectivas de Género

En la educación inglesa, persisten brechas de género significativas que afectan tanto los logros académicos como las elecciones de asignaturas, especialmente en áreas STEM (ciencia, tecnología, ingeniería y matemáticas). Este análisis explora cómo estas disparidades se manifiestan a lo largo del sistema educativo y sus implicaciones a largo plazo.

Disparidades en Logros Académicos

En las primeras etapas de la educación (Key Stage 2), se observan diferencias notables en los logros académicos entre niños y niñas. Las niñas superan a los niños en lectura y escritura, alcanzando niveles superiores con mayor frecuencia. Sin embargo, en matemáticas, ambos géneros muestran rendimientos similares, sin diferencias significativas en las tasas de logro.

Al avanzar hacia Key Stage 4 (GCSEs), estas tendencias persisten. Las niñas continúan destacándose en asignaturas como inglés, obteniendo más calificaciones A*-C en comparación con los niños. En contraste, en matemáticas y ciencias, la diferencia se reduce, con rendimientos relativamente equitativos entre géneros. Estos resultados sugieren que, aunque las niñas tienen un rendimiento superior en materias lingüísticas, no logran una ventaja equivalente en STEM.

##Influencia en la Elección de Asignaturas La elección de asignaturas en la educación secundaria refleja y amplifica estas disparidades. Las niñas son significativamente menos propensas a elegir asignaturas STEM, inclinándose más hacia humanidades y artes. Este fenómeno se debe en parte a la falta de modelos a seguir femeninos en STEM y a estereotipos de género que persisten tanto en el entorno educativo como en la sociedad en general.

Investigaciones indican que las actitudes hacia las matemáticas y la ciencia se forman a temprana edad y están fuertemente influenciadas por las expectativas y creencias de los padres y educadores. Las niñas que no ven a mujeres en roles STEM pueden internalizar la idea de que estas áreas no son para ellas, limitando sus aspiraciones y decisiones académicas futuras.

Implicaciones y Recomendaciones

Estas disparidades afectan el rendimiento académico inmediato, y también tienen implicaciones a largo plazo en las oportunidades de carrera y la equidad de género en el mercado laboral. Las mujeres siguen estando subrepresentadas en profesiones STEM, lo que contribuye a una brecha salarial de género y limita el potencial de innovación y crecimiento económico.

Para abordar estas desigualdades, hay que implementar políticas y prácticas que promuevan la participación femenina en STEM desde una edad temprana. Esto incluye:

  • Modelos identificatorios: Aumentar la visibilidad de mujeres en STEM a través de programas de tutoría y eventos donde profesionales femeninas compartan sus experiencias.

  • Capacitación docente: Formar al grupo de docentes para reconocer y contrarrestar sesgos implícitos que puedan influir en la percepción de las capacidades de las niñas en STEM.

  • Intervenciones educativas: Diseñar programas educativos que fomenten el interés y la confianza de las niñas en las materias STEM, utilizando métodos de enseñanza inclusivos y atractivos.

  • Políticas institucionales: Desarrollar políticas a nivel institucional que promuevan la igualdad de género y proporcionen recursos adecuados para apoyar a las estudiantes en su trayectoria académica y profesional en STEM.

Conclusión

Cerrar la brecha de género en los logros académicos y la elección de asignaturas es esencial para fomentar una sociedad más equitativa. A través de esfuerzos coordinados que aborden las raíces culturales y estructurales de estas desigualdades, podemos crear un entorno educativo que empodere a todas las personas, independientemente de su género, para alcanzar su máximo potencial en cualquier campo de su elección.

Resumen

In common with other OECD countries, there is a gender gap in educational achievement in England favouring girls. This carries through to tertiary education. On the other hand, boys are far more likely to engage in STEM in post-16 vocational education and at university. The underachievement of boys overall, but over-representation in STEM, presents significant challenges for policy. This paper documents changes in the gender gap over the last 20 years in England and discusses findings in the light of international evidence. It concludes that education policies, in academic and in vocational spheres, can be designed to reduce gender inequalities that exist in both.

El documento 'graa050.pdf' contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positive. Los temas clave que surgen del análisis incluyen gender gap, 0.001 0.001, 10 july, 36 4, 4 816. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad. Las principales oraciones del documento son: 21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets. | Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance. | This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time. | The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school. | The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).. Un análisis comparativo entre la palabra más positiva ('achievement') y la más negativa ('difficult') se muestra en el gráfico adjunto. El documento 'graa050.pdf' contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positive. Los temas clave que surgen del análisis incluyen gender gap, 0.001 0.001, 10 july, 36 4, 4 816. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad. Las principales oraciones del documento son: 21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets. | Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance. | This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time. | The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school. | The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).. Un análisis comparativo entre la palabra más positiva ('achievement') y la más negativa ('limited') se muestra en el gráfico adjunto.
Parsing text into sentences and tokens...DONE
Calculating pairwise sentence similarities...DONE
Applying LexRank...DONE
Formatting Output...DONE


LexRank Summary:
21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets.
Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance.
This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time.
The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school.
The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).
Summary:
El documento 'graa050.pdf' contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positive. Los temas clave que surgen del análisis incluyen gender gap, 0.001 0.001, 10 july, 36 4, 4 816. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad. Las principales oraciones del documento son: 21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets. | Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance. | This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time. | The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school. | The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).. Un análisis comparativo entre la palabra más positiva ('achievement') y la más negativa ('difficult') se muestra en el gráfico adjunto. El documento 'graa050.pdf' contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positive. Los temas clave que surgen del análisis incluyen gender gap, 0.001 0.001, 10 july, 36 4, 4 816. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad. Las principales oraciones del documento son: 21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets. | Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance. | This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time. | The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school. | The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).. Un análisis comparativo entre la palabra más positiva ('achievement') y la más negativa ('limited') se muestra en el gráfico adjunto.

Word Count: 5592 

Sentiment Analysis:
       anger anticipation      disgust         fear          joy      sadness 
          26           53           16           34           40           32 
    surprise        trust     negative     positive 
          22          102           65          170 

Plots:

Referencias

El documento 'graa050.pdf' contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positive. Los temas clave que surgen del análisis incluyen gender gap, 0.001 0.001, 10 july, 36 4, 4 816. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad. Las principales oraciones del documento son: 21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets. | Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance. | This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time. | The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school. | The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).. Un análisis comparativo entre la palabra más positiva ('achievement') y la más negativa ('difficult') se muestra en el gráfico adjunto. El documento 'graa050.pdf' contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positive. Los temas clave que surgen del análisis incluyen gender gap, 0.001 0.001, 10 july, 36 4, 4 816. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad. Las principales oraciones del documento son: 21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets. | Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance. | This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time. | The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school. | The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).. Un análisis comparativo entre la palabra más positiva ('achievement') y la más negativa ('limited') se muestra en el gráfico adjunto.
Parsing text into sentences and tokens...DONE
Calculating pairwise sentence similarities...DONE
Applying LexRank...DONE
Formatting Output...DONE


LexRank Summary:
21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets.
Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance.
This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time.
The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school.
The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).

Analysis Summary

El documento 'graa050.pdf' contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positive. Los temas clave que surgen del análisis incluyen gender gap, 0.001 0.001, 10 july, 36 4, 4 816. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad. Las principales oraciones del documento son: 21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets. | Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance. | This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time. | The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school. | The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).. Un análisis comparativo entre la palabra más positiva ('achievement') y la más negativa ('difficult') se muestra en el gráfico adjunto. El documento 'graa050.pdf' contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positive. Los temas clave que surgen del análisis incluyen gender gap, 0.001 0.001, 10 july, 36 4, 4 816. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad. Las principales oraciones del documento son: 21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets. | Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance. | This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time. | The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school. | The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).. Un análisis comparativo entre la palabra más positiva ('achievement') y la más negativa ('limited') se muestra en el gráfico adjunto.

Word Cloud

21 For example, boys were found to be interested in explosives and engines, whereas girls were more

interested in the environment and healthy living: https://www.roseproject.no/publications/english-pub.html

Appendix
                                                                                                                                                                        832




Table A1: Summary statistics of educational outcomes and gender gaps by group

                                              Overall                            FSM                             Black                            Asian

                                  Males    Females Gender gap Males         Females Gender gap Males         Females Gender gap       Males Females Gender gap

Key Stage 2 (KS2)
Target achieved in KS2 reading    0.83    0.88           –0.05      0.71      0.79        –0.07      0.81      0.87        –0.06      0.83      0.87       –0.04
Target achieved in KS2 writing    0.79    0.89           –0.10      0.65      0.79        –0.14      0.78      0.88        –0.10      0.82      0.89       –0.07
Target achieved in KS2 maths      0.85    0.85            0.00      0.74      0.74         0.00      0.81      0.83        –0.02      0.86      0.85        0.01
Achieved L5+ in KS2 reading       0.41    0.48           –0.07      0.25      0.30        –0.05      0.33      0.42        –0.09      0.37      0.42       –0.05
Achieved L5+ in KS2 writing       0.23    0.38           –0.14      0.11      0.21        –0.10      0.19      0.33        –0.14      0.25      0.37       –0.12
Achieved L5+ in KS2 maths         0.43    0.39            0.04      0.26      0.23         0.04      0.35      0.34         0.01      0.47      0.42        0.06
Key Stage 4 (GCSEs)
5+ A*–C GCSEs or equivalents      0.8     0.86           –0.07      0.65      0.74        –0.09      0.8       0.86        –0.07      0.84      0.90       –0.06
5+ A*–C GCSEs                     0.51    0.63           –0.12      0.27      0.37        –0.11      0.47      0.62        –0.15      0.57      0.69       –0.12
A*–C English GCSE                 0.61    0.76           –0.15      0.39      0.55        –0.16      0.6       0.76        –0.15      0.64      0.78       –0.13
A*–C maths GCSE                   0.71    0.72           –0.01      0.5       0.51        –0.01      0.67      0.7         –0.03      0.76      0.77       –0.01
A*–A maths GCSE                   0.19    0.19            0.00      0.07      0.07         0.00      0.14      0.15        –0.01      0.28      0.27        0.01
A*–A English GCSE                 0.11    0.21           –0.10      0.03      0.08        –0.04      0.07      0.16        –0.09      0.11      0.22       –0.10
Post-16
Not observed in education at 18   0.13    0.1             0.03      0.2       0.17         0.03      0.1       0.06         0.03      0.09      0.06        0.02
NEET at 18                        0.07    0.05            0.02      0.13      0.11         0.02      0.07      0.04         0.03      0.06      0.05        0.01
Achieved Level 2 or more          0.9     0.94           –0.04      0.79      0.86        –0.07      0.91      0.95        –0.04      0.92      0.95       –0.03
Achieved Level 3 or more          0.63    0.74           –0.11      0.43      0.54        –0.11      0.72      0.83        –0.11      0.75      0.84       –0.09
Apprenticeship                    0.2     0.16            0.04      0.15      0.15         0.00      0.09      0.07         0.02      0.08      0.07        0.00
University degree or more         0.22    0.31           –0.08      0.12      0.18        –0.06      0.29      0.42        –0.13      0.36      0.45       –0.09
Subject choice
Any STEM in FE                    0.70    0.60            0.10      0.65    0.54           0.11      0.67    0.64           0.03      0.84    0.77          0.07
Any STEM vocational (FE)          0.29    0.13            0.16      0.35    0.16           0.19      0.29    0.16           0.13      0.37    0.20          0.16
Any STEM academic (FE)            0.55    0.55            0.00      0.44    0.46          –0.02      0.51    0.57          –0.06      0.68    0.70         –0.02
STEM for those in HE              0.47    0.25            0.22      0.47    0.24           0.23      0.44    0.23           0.21      0.45    0.27          0.19
N                               291,210 280,341                    43,357 41,859                    13,637 13,806                    25,100 23,966

Notes: Data come from the National Pupil Database, Individual Learner Records, and Higher Education Statistics Agency datasets.
Two policy concerns arise from these observations: (a) why do males underachieve in

     *Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
c.cavaglia@lse.ac.uk
     **Centre for Economic Performance and Centre for Vocational Education Research and Department of
Economics, LSE; e-mail: s.j.machin@lse.ac.uk
     ***Centre for Economic Performance and Centre for Vocational Education Research, LSE and
University of Surrey; e-mail: s.mcnally@surrey.ac.uk
     ****Centre for Economic Performance and Centre for Vocational Education Research, LSE; e-mail:
j.ruiz-valenzuela@lse.ac.uk
     This work was supported by the Centre for Vocational Education Research (funded by the Department of
Education) and the Economic and Social Research Council through the Centre for Economic Performance.
This
has relevance to education systems in Europe because as noted by Pekkarinen (2012),
many boys are going through adolescence at the age of 15/16 at which some coun-
tries (including the UK) are tracking students to different pathways—and this is a

Gender, achievement, and subject choice in English education                                              829


potential explanation for why gender gaps in attainment are lower in countries that
track students at an earlier age.17 The exam at age 16 in England is very high stakes
and perhaps that was understandable in the 1950s when O-levels (the predecessor of
GCSEs) were set up as it was common for individuals to enter the labour market after
this time.
The main
driver of differences between the raw gender gap and the gap after including controls is
prior attainment at age 7.9 The results including controls reflect how the gender gap in
maths becomes wider over time at primary school.
The gender gap in Panel
A (not being observed in education at age 18 and being classified as NEET) is fully
accounted for by including these controls (about half is accounted for by achievement
at the end of primary school and half by achievement at the end of secondary school,
with little additional role for institutional-level variables).
Nota

El documento ‘graa050.pdf’ contiene 5592 palabras y se centra principalmente en –, gender, education, gap, school, stem, age, boys, girls, maths. El texto exhibe un tono predominantemente positivo. Las palabras que más contribuyen al sentimiento positivo son achievement, important, well, free, good, mientras que las que más contribuyen al sentimiento negativo son difficult, limited, errors, problems, bad.

Reutilización

Cómo citar

BibTeX
@online{robano2024,
  author = {Robano, Virginia},
  title = {Resumen del artículo Gender, achievement, and subject choice
    in English education},
  date = {2024-07-10},
  url = {https://ceibal-fichas-genero-stem.netlify.app/posts/Inglaterra, gender, achievement and subjet choice/},
  langid = {es}
}
Por favor, cita este trabajo como:
Robano, Virginia. 2024. “Resumen del artículo Gender, achievement, and subject choice in English education.” July 10, 2024. https://ceibal-fichas-genero-stem.netlify.app/posts/Inglaterra, gender, achievement and subjet choice/.