Resumen del artículo Tech-Savvy Men and Caring Women: Middle School Students’ Gender Stereotypes Predict Interest in Tech-Education

publicado en Sex Roles (2023)

sesgos implícitos
sesgos explícitos
estereotipos
tecnología
interés
docentes
estudiantes
teoría del rol social
cultura
teoría del valor esperado
secundaria
análisis empírico
estereotipos de género implícitos
estereotipos de género explícitos
cuidado
prueba de asociación implícita
solidaridad
paradoja de equidad de género
teoría de la estratificación de género
iat
Autor/a
Fecha de publicación

8 de abril de 2024

Fecha de modificación

23 de septiembre de 2024

Resumen

El mercado laboral está fuertemente segregado por género, con pocas mujeres trabajando en el sector tecnológico (por ejemplo, TI) y pocos hombres trabajando en el sector de cuidados (por ejemplo, enfermería). El trabajo testea la hipótesis de que los estudiantes de secundaria asocian fuertemente la tecnología con los hombres y el cuidado con las mujeres en el contexto de Suecia (un país que obtiene una puntuación alta en los índices de igualdad de género), y que estos estereotipos de género para la tecnología se relacionan con el menor interés de las niñas en la tecnología.Medimos los estereotipos de género sobre tecnología/cuidado con medidas implícitas (la Prueba de Asociación Implícita) y explícitas (autoinforme) en una muestra de estudiantes de secundaria (n = 873). Los resultados respaldan las hipótesis principales y corroboran la teoría del valor de las expectativas de Eccles, lo que indica que el respaldo de estereotipos de género implícitos puede servir como barrera para que las mujeres sigan carreras profesionales de tipo masculino. Además, una muestra de profesores de secundaria (n = 86) mostró estereotipos de género implícitos más fuertes que los estudiantes. Inesperadamente, las niñas de secundaria de origen extranjero no mostraron estereotipos de género implícitos, lo que analizan en relación con la paradoja de la igualdad de género. Estos hallazgos sugieren que para satisfacer las necesidades de contratación de un mundo cada vez más digitalizado, la industria tecnológica y otras partes interesadas deberían esforzarse en contrarrestar el estereotipo de que la tecnología es para hombres.

Advertencia

n = 873 estudiantes de secundaria

n = 86 docentes

Resumen visual del documento

Parsing text into sentences and tokens...DONE
Calculating pairwise sentence similarities...DONE
Applying LexRank...DONE
Formatting Output...DONE
[1] "The stereotype that Agency and Things (Technology) women are more communal than men holds well over time (Ellemers, 2018; Haines et al., 2016) and also in Sweden Agency refers to the desire and motivation for mastery and (Gustafsson Sendén et al., 2019), and studies show the independence and is associated with traits such as asser- corresponding gender differences in students’ communal tiveness and competence (e.g., Abele & Wojciske, 2014)."                                                           
[2] "Historical events may have played a role Also, since the teacher sample was small in this study, in shaping a gender-segregated labor market which led to it should be replicated with larger samples of teachers, and the development of strong gender stereotypes despite reduc- other adults, to test if adults generally have stronger implicit tions in male-primacy associations (i.e., attitudes privileging technology and caregiving gender stereotypes than children men over women, Knight & Brinton, 2017)."
[3] "Sex Roles (2023) 88:307–325 https://doi.org/10.1007/s11199-023-01353-1 ORIGINAL ARTICLE Tech-Savvy Men and Caring Women: Middle School Students’ Gender Stereotypes Predict Interest in Tech-Education Una Tellhed1 · Fredrik Björklund1 · Kalle Kallio Strand1 Accepted: 13 December 2022 / Published online: 11 March 2023 © The Author(s) 2023 Abstract The labor market is strongly gender segregated with few women working in the tech sector (e.g., IT) and few men working in the care sector (e.g., nursing)." 
[4] "We suggest adding a how gender stereotypes may hinder career interest devel- measure of interest in the care sector in future replications, opments, we recommend investigating the relationship to test whether students’ implicit associations of gender with between tech gender stereotypes and factors that impact technology versus caregiving also relate to gender differ- career interest."                                                                                                                    
[5] "Since the tech sector has higher stronger in more gender-equal countries, this may hinder status than the care sector (e.g., Block et al., 2018a; Croft et tech-interest (“things”-interest) development for girls, and 13 320 Sex Roles (2023) 88:307–325 subsequently lead to fewer young women studying tech- effects of gender and nationality/ethnicity on technology educations, as compared to less gender-equal countries and caregiving stereotypes."                                                          
[6] "The main aim by a multitude of factors (see Eccles, 1987, 1994; Eccles & is to investigate if students endorse stereotypes for tech- Wigfield, 2020; Master & Meltzoff, 2020 for reviews) and nology and caregiving careers according to gender, and if some studies have shown that interest may be the strongest their implicit associations along these dimensions relate to predictor of career choice (Maltese & Tai, 2011; Rundgren their interest in pursuing a tech-education in the future."                   
[7] "Keywords Implicit gender stereotypes · Explicit gender stereotypes · Technology · Caregiving · Implicit association test · Expectancy value theory · Social role theory · Adolescents · Teachers · Interest · STEM · HEED The labor market is horizontally gender segregated, where et al., 2014; Lippa et al., 2014; Su et al., 2009)."                                                                                                                                                                                

Parsing text into sentences and tokens...DONE
Calculating pairwise sentence similarities...DONE
Applying LexRank...DONE
Formatting Output...DONE
 [1] "We tested the hypothesis that middle school students strongly associate technology with\nmen and caregiving with women in a Swedish context (i.e., a country that scores high in gender equality indices), and\nthat these gender stereotypes for tech relate to girls’ lower interest in tech-focused education."                                                                                                                                                                                                                                                                                                                                                                                                                           
 [2] "Keywords Implicit gender stereotypes · Explicit gender stereotypes · Technology · Caregiving · Implicit association\ntest · Expectancy value theory · Social role theory · Adolescents · Teachers · Interest · STEM · HEED\n\n\nThe labor market is horizontally gender segregated, where              et al., 2014; Lippa et al., 2014; Su et al., 2009)."                                                                                                                                                                                                                                                                                                                                                                                  
 [3] "The main aim\nby a multitude of factors (see Eccles, 1987, 1994; Eccles &        is to investigate if students endorse stereotypes for tech-\nWigfield, 2020; Master & Meltzoff, 2020 for reviews) and           nology and caregiving careers according to gender, and if\nsome studies have shown that interest may be the strongest         their implicit associations along these dimensions relate to\npredictor of career choice (Maltese & Tai, 2011; Rundgren          their interest in pursuing a tech-education in the future."                                                                                                                                                                                                  
 [4] "relate to students’ tech interest, but due to social desirabil-\n    Social role theory (SRT, Eagly, 1987, Koenig &                 ity concerns associated with explicit measures, predictions\nEagly, 2014) also connects gender stereotypes to gender\n\n\n\n13\n\nSex Roles (2023) 88:307–325                                                                                                  309\n\n\nfor these measures are less straightforward (Dovidio et al.,     SRT, we expect that the students in this study would gener-\n2003)."                                                                                                                                                                                            
 [5] "To conclude, since the care sector and the tech\n(Eagly, 1987), the core of current gender stereotypes may         sector are strongly gender skewed in Sweden, we hypoth-\nthus reflect the typical occupational roles for “people” and      esize that there would be strong gender stereotypes differen-\n“things” associated with women and men in Western labor           tially associated with these two sectors."                                                                                                                                                                                                                                                                                                                    
 [6] "For age, extensive data have shown stronger implicit               For gender, although both men and women generally\ngender-science stereotypes in older generations as com-            show gender stereotyped associations on the IAT (Miller\npared to younger (see Charlesworth & Banaji, 2019, for a           et al., 2015; see also Charlesworth & Banaji, 2019, for a\nreview)."                                                                                                                                                                                                                                                                                                                                                    
 [7] "Specifically, the teach-\npoint in the expected direction, d = 0.75–1.79, indicating                  ers reported stronger societal gender stereotypes than the\nthat the students believe that people in Sweden think that                  students, except for the nonsignificant difference between\nmen have stronger technical ability than women and women                    teachers’ and Grade 8 students’ societal tech stereotypes\nhave stronger caregiving ability than men, which supported                  (see Table 3)."                                                                                                                                                                                                 
 [8] "The results showed that the teachers had much\nin girls corroborates EEVT, SEVT and STEMO, which state                stronger implicit technology/caregiving gender stereotypes\nthat gender stereotypes may serve as a barrier to develop-             than the students, and the youngest students had the weakest\ning an interest in tech-focused careers for girls and women,           associations."                                                                                                                                                                                                                                                                                                                                 
 [9] "Since the tech sector has higher       stronger in more gender-equal countries, this may hinder\nstatus than the care sector (e.g., Block et al., 2018a; Croft et   tech-interest (“things”-interest) development for girls, and\n\n\n\n                                                                                                                       13\n\n320                                                                                                       Sex Roles (2023) 88:307–325\n\n\nsubsequently lead to fewer young women studying tech-              effects of gender and nationality/ethnicity on technology\neducations, as compared to less gender-equal countries             and caregiving stereotypes."
[10] "Historical events may have played a role             Also, since the teacher sample was small in this study,\nin shaping a gender-segregated labor market which led to           it should be replicated with larger samples of teachers, and\nthe development of strong gender stereotypes despite reduc-        other adults, to test if adults generally have stronger implicit\ntions in male-primacy associations (i.e., attitudes privileging    technology and caregiving gender stereotypes than children\nmen over women, Knight & Brinton, 2017)."                                                                                                                                                                                 

El siguiente gráfico muestra una analogía al estudio “she giggles, he gallops” donde cuentan los bigramas que coinciden con “él X” y “ella X”.

En este caso, buscamos las palabras “stereotypes” y “tech”.

La idea de la relación logarítmica muestra la probabilidad de que aparezca una palabra en comparación con su contraparte (por lo que “stereotypes (algo)” tiene aproximadamente 5 más probabilidades de aparecer que “tech (algo)”. En este gráfico, reemplazamos las etiquetas del eje x con “2x” y “4x”, pero sin ellos, se obtienen números como 1, 2 y 3 (o -1, -2, -3)). Para convertir esos números de razones registradas a la versión multiplicativa (es decir, 2x en lugar de 1), eleva 2 a la potencia de la razón logarítmica. Si la relación logarítmica es 3, la versión legible por humanos es 2^3, o sea 8 veces.

Referencias

Tellhed, U., Björklund, F. & Kallio Strand, K. Tech-Savvy Men and Caring Women: Middle School Students’ Gender Stereotypes Predict Interest in Tech-Education. Sex Roles 88, 307–325 (2023).

Reutilización

Cómo citar

BibTeX
@online{robano2024,
  author = {Robano, Virginia},
  title = {Resumen del artículo Tech-Savvy Men and Caring Women: Middle
    School Students’ Gender Stereotypes Predict Interest in
    Tech-Education},
  date = {2024-04-08},
  url = {https://ceibal-fichas-genero-stem.netlify.app/posts/estereotipos/},
  langid = {es}
}
Por favor, cita este trabajo como:
Robano, Virginia. 2024. “Resumen del artículo Tech-Savvy Men and Caring Women: Middle School Students’ Gender Stereotypes Predict Interest in Tech-Education.” April 8, 2024. https://ceibal-fichas-genero-stem.netlify.app/posts/estereotipos/.