DataPDF Available
Appendix A
Pretest on the stereotypicality of professions
English
German
(feminine-masculine word pairs)
Italian
(feminine-masculine word pairs)
Typically feminine professions
dancers
Tänzerinnen und Tänzer
danzatrici e danzatori
M = 2.73, SD = .96
hairdressers
Friseurinnen und Friseure
parrucchiere e parrucchieri
M = 2.97, SD = 1.08
interpreters
Dolmetscherinnen und Dolmetscher
traduttrici e traduttori
M = 3.14, SD = 1.06
nutritionists
Ernährungsberaterinnen und
Ernährungsberater
nutrizioniste e nutrizionisti
M = 3.22, SD = .98
pharmacists
Apothekerinnen und Apotheker
farmaciste e farmacisti
M = 3.38, SD = .95
psychologists
Psychologinnen und Psychologen
psicologhe e psicologi
M = 3.08, SD = 1.16
tailors
Schneiderinnen und Schneider
sarte e sarti
M = 2.86, SD = 1.09
Typically masculine professions
butchers
Fleischerinnen und Fleischer
M = 6.02, SD = .99
macellaie e macellai
M = 6.07, SD = .93
electricians
Elektrikerinnen und Elektriker
M = 6.22, SD = .76
elettriciste ed elettricisti
M = 6.51, SD = .94
brick layers
Maurerinnen und Maurer
M = 6.46, SD = .71
muratrici e muratori
M = 6.68, SD = .90
mechanics
Mechanikerinnen und Mechaniker
M = 6.12, SD = .93
meccaniche e meccanici
M = 6.51, SD = .95
computer
scientists
Informatikerinnen und Informatiker
M = 5.81, SD = 1.08
informatiche ed informatici
M = 5.31, SD = 1.00
truckers
Lastwagenfahrerinnen und
Lastwagenfahrer
M = 6.34, SD = .82
camioniste e camionisti
M = 6.27, SD = .87
engineers
Ingenieurinnen und Ingenieure
M = 5.39, SD = 1.11
ingegnere ed ingegneri
M = 5.08, SD = 1.18
Slightly masculine professions
bakers
Bäckerinnen und Bäcker
M = 4.98, SD = 1.13
panettiere e panettieri
M = 5.15, SD = 1.28
bankers
Bankerinnen und Banker
M = 5.07, SD = 1.03
banchiere e banchieri
M = 5.25, SD = 1.08
chefs
Köchinnen und Köche
M = 4.56, SD = .98
cuoche e cuochi
M = 4.62, SD = 1.12
farmers
Bäuerinnen und Bauern
M = 4.66, SD = 1.02
contadine e contadini
M = 4.90, SD = 1.09
mathematicians
Mathematikerinnen und Mathematiker
M = 5.37, SD = 1.02
matematiche e matematici
M = 4.78, SD = 1.18
physicians
Physikerinnen und Physiker
M = 5.39, SD = 1.12
fisiche e fisici
M = 4.93, SD = 1.11
Gender-neutral professions
gynecologists
Gynäkologinnen und Gynäkologen
M = 4.39, SD = 1.32
ginecologhe e ginecologi
M = 3.56, SD = 1.05
historians
Historikerinnen und Historiker
M = 4.49, SD = 1.05
storiche e storici
M = 4.47, SD = 1.25
pediatricians
Kinderärztinnen und Kinderärzte
M = 3.85, SD = 1.04
pediatre e pediatri
M = 3.58, SD = .95
Professions rated differently by the German and Italian pretest samples
letter carriers
Briefträgerinnen und Briefträger
M = 5.14, SD = .96
postine e postini
M = 4.14, SD = 1.12
librarians
Bibliothekarinnen und Bibliothekare
M = 3.49, SD = 1.16
bibliotecarie e bibliotecari
M = 3.54, SD = 1.16
salespersons
Verkäuferinnen und Verkäufer
M = 2.85, SD = .99
venditrici e venditori
M = 3.97, SD = .95
waiters
Kellnerinnen und Kellner
M = 3.34, SD = .96
cameriere e camerieri
M = 3.97, SD = .83
Appendix B
Target professions used in the main study, with stereotypicality of profession and
distribution to list of professions.
Stereotypicality of Profession
List of
professions
Typically feminine professions
Typically masculine
professions
List 1
Hair dressers
Psychologists
Mechanics
Physisicts
List 2
Tailors
Interpreters
Electricians
Computer scientists
List 3
Dancers
Nutrition scientists
Truckers
Engineers
Appendix C
Further results, which do not involve linguistic form
MANOVA
The analysis revealed a main effect of stereotypicality of professions, F(5, 354) = 699.84, p <
.001, η2p = .91, an interaction effect of stereotypicality of profession and participant gender,
F(5, 354) = 3.40, p = .005, η2p = .05, stereotypicality of profession and list, F(10, 710) =
11.79, p < .001, η2p = .14, stereotypicality of profession and language, F(5,354) = 3.52, p =
.004, η2p = .05, stereotypicality of profession, list and language, F(10, 710) = 2.06, p = .026,
η2p = .03. Furthermore, a main effect of the list-factor F(10, 710) = 3.64, p < .001, η2p = .05, a
main effect of language, F(5, 354) = 5.56, p < .001, η2p = .07, and an interaction of list and
language, F(10, 710) = 2.69, p = .003, η2p = .04 reached significance.
ANOVAS
Perceived social status
The ANOVA for social status revealed a main effect of stereotypicality of profession, F(1,
363) = 29.84, p < .001, η2p = .08, indicating that feminine professions were ascribed lower
social status (M = 3.94) than masculine professions (M = 4.24). The interaction effect of
stereotypicality of profession and language was significant, F(1, 363) = 7.72, p = .006, η2p =
.02. Pairwise comparisons indicated that feminine professions were ascribed lower social
status than masculine professions in German (Mfem.prof .= 3.99 vs. Mmasc.prof. = 4.39, p < .001,
η2p = .09). Furthermore, the main effect of list, F(2, 363) = 4.22, p = .015, η2p = .02 reached
significance, but was qualified by the interaction between stereotypicality of profession and
list, F(2, 363) = 3.62, p = .028, η2p = .02. Pairwise comparisons indicated that feminine
professions were ascribed significantly lower social status than masculine professions on list
1 (Mfem.prof .= 3.97 vs. Mmasc.prof. = 4.37, p .001, η2p = .05) and list 2 (Mfem.prof .= 4.17 vs.
Mmasc.prof. = 4.33, p .001, η2p = .04), but not in list 3 (Mfem.prof .= 3.95 vs. Mmasc.prof. = 4.01, p =
.332, η2p = .003).
Estimated salary
The ANCOVA revealed a significant main effect for stereotypicality of professions, F(1,
359) = 137.03, p .001, η2p = .28. Salaries of feminine professions (M = 6.12) were estimated
to be lower than salaries of masculine professions (M = 6.91). Moreover, there was a
significant interaction between stereotypicality of profession and language, F(1, 359) =
17.90, p .001, η2p = .05. Feminine professions were estimated to have lower salaries both in
German (p .001, η2p = .27) and Italian (p .001, η2p = .07); salary estimations for masculine
profession were higher by German-speaking participants (M = 7.08) than by Italian-speaking
participants (M = 6.74) (p = .002, η2p = .03).
Women’s visibility
The ANOVA revealed a significant main effect for stereotypicality of professions, F(1, 361)
= 3489.12, p .001, η2p = .91. Women’s visibility was higher in feminine professions (M =
2.02) than in masculine professions (M = -2.07). A significant main effect for language, F(1,
361) = 7.81, p = .005, η2p = .02, indicated that women’s visibility was generally lower in
Italian professions (M = -.11) than in German professions (M = .03). A main effect of the list
factor, F(1, 361) = 7.55, p .001, η2p = .04, indicated that women’s visibility was generally
higher in all professions on list 1 than in both list 2 (p = .018) and list 3 (p .001). Lists 2
and 3 did not differ in this respect (p = .809).
The significant three-way-interaction between stereotypicality, language and list factor, F(2,
361) = 3.81, p = .023, η2p = .02, indicated that (a) women’s visibility in feminine professions
was rated higher than in masculine professions in both languages across all lists (all ps
.001). Only considering differences within languages, pairwise comparisons showed for
German, that (b) women’s visibility was rated higher for masculine professions on list 1 (e.g.
mechanic & physicist) than for list 3 (e.g., truckers and engineers) (p = .002). In Italian,
women’s visibility of masculine professions on list 2 was rated higher than on list 3 (p =
.012).
Ascribed competence
The ANOVA showed a significant main effect of stereotypicality of profession, F(1, 363) =
14.26, p .001, η2p = .04. Masculine professions (M = 4.99) were ascribed more competence
than feminine professions (M = 4.87). All means and standard deviations are reported in
Table 6. Moreover, the interaction effect between stereotypicality of profession and
participant gender reached significance, F(1, 363) = 6.65, p = .010, η2p = .02. This effect was
driven by the fact that men ascribed typically feminine professions less competence (M =
4.82) than masculine professions (M = 4.97), p .001. The significant interaction of
stereotypicality and list, F(2, 363) = 13.41, p .001, η2p = .07, indicated that only for list 1
competence ascriptions were higher for feminine professions than for masculine professions
(p .001). The interaction also goes back to differences between competence ascriptions
between lists: typically feminine professions from list 2 were ascribed more competence than
feminine professions on list 1 (p = .008).
Ascribed warmth
The main effect for stereotypicality was significant, F(1, 363) = 209.44, p = .001, η2p = .37.
Typically feminine professions (M = 4.53) were perceived as warmer than masculine
professions (M = 3.74). The main effect for language, F(1, 363) = 13.71, p .001, η2p = .04,
indicated that German participants generally ascribed more warmth to professional groups (M
= 4.27) than Italian participants (M = 3.96). Moreover, the interaction between
stereotypicality and list was significant, F(2, 363) = 6.96, p .001, η2p = .04. All feminine
professions were ascribed more warmth than masculine professions across all lists (all ps
.001). Additionally, there were differences between the warmth perceptions of typically
feminine professions across lists: feminine professions on list 1 were perceived to be warmer
than professions on list 2 (p = .007) and list 3 (p = .010). There were no differences for
masculine professions across lists.
__________________________
1 After measuring the dependent variables we also assessed participants’ attitudes towards
gender-fair language (Sczesny, Moser, and Wood, 2015) and sexism (with the Ambivalent
Sexism Inventory; Glick and Fiske, 1996). Since both attitude scales were correlated with the
dependent as well as the independent variables, we could not use them as moderators, as had
been intended, and thus do not report them here.

File (1)

ResearchGate has not been able to resolve any citations for this publication.
ResearchGate has not been able to resolve any references for this publication.