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── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag() masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
From Table 3 of Pownall, M., & Heflick, N. (2023). Mr. Active and Little Miss Passive? The Transmission and Existence of Gender Stereotypes in Children’s Books. Sex Roles. https://doi.org/10.1007/s11199-023-01409-2
<- "Bad 3.18 0.48 1.59 0.61 Bossy 2.50 0.77 1.98 0.61 Brainy 2.96 0.45 4.12 0.71 Brave 3.39 0.66 4.21 0.77 Busy 2.68 0.54 3.04 0.64 Chatterbox 2.19 0.63 2.71 0.84 Cheerful 2.87 0.44 4.56 0.60 Clever 2.99 0.36 4.22 0.69 Clumsy 3.02 0.62 2.22 0.69 Contrary 2.66 0.78 2.25 0.74 Cool 3.31 0.61 4.03 0.74 Curious 2.84 0.56 3.96 0.66 Daydream 2.67 0.62 3.18 0.92 Dizzy 2.38 0.58 2.45 0.71 Dotty 2.26 0.60 2.67 0.75 Fickle 2.52 0.64 1.95 0.59 Forgetful 2.97 0.56 2.11 0.57 Fun 2.95 0.37 4.57 0.64 Funny 3.05 0.41 4.50 0.56 Fussy 2.47 0.74 1.98 0.65 Giggles 2.03 0.56 4.25 0.72 Good 2.93 0.33 4.53 0.70 Greedy 3.31 0.53 1.64 0.65 Grumble 3.45 0.63 1.98 0.51 Grumpy 3.54 0.66 1.71 0.61 Happy 2.88 0.42 4.74 0.54 Helpful 2.65 0.49 4.47 0.60 Hug 2.54 0.62 4.59 0.60 Lazy 3.38 0.54 1.65 0.66 Lucky 2.98 0.36 4.10 0.73 Magic 2.78 0.60 4.15 0.75 Mean 3.02 0.55 1.46 0.63 Messy 3.19 0.69 2.03 0.62 Mischief 3.21 0.70 2.66 0.80 Muddle 2.86 0.46 2.31 0.63 Naughty 3.12 0.68 2.22 0.77 Neat 2.64 0.59 3.67 0.75 Noisy 3.18 0.63 2.29 0.70 Nonsense 3.05 0.47 2.22 0.78 Nosey 2.49 0.68 2.14 0.65 Perfect 2.73 0.59 4.09 1.06 Princess 1.32 0.55 3.13 1.13 Quick 2.99 0.48 3.48 0.65 Quiet 2.82 0.49 2.98 0.55 Rude 3.29 0.57 1.18 0.43 Rush 2.93 0.62 2.63 0.62 Scary 3.23 0.54 1.73 0.72 Scatterbrain 2.39 0.64 2.22 0.68 Shy 2.72 0.62 2.79 0.56 Silly 2.93 0.68 2.71 0.83 Skinny 2.51 0.64 2.73 0.80 Slow 3.18 0.48 2.32 0.63 Small 2.70 0.54 2.90 0.48 Splendid 2.89 0.59 4.45 0.69 Strong 3.52 0.74 4.13 0.67 Stubborn 3.08 0.69 2.12 0.71 Tall 3.50 0.60 3.23 0.61 Tidy 2.76 0.49 3.94 0.74 Tiny 2.39 0.61 3.06 0.57 Trouble 3.28 0.65 1.69 0.65 Uppity 2.78 0.71 1.83 0.69 Wise 3.09 0.58 4.40 0.60 Worry 2.68 0.56 2.02 0.65 Wrong 3.11 0.44 1.78 0.70"
Copying from the pdf removed line breaks (it would have been fine had I copied from the html – anyway…). Turn raw_dat into a data frame and calculate the binariness index.
<- strsplit (raw_dat, " " )[[1 ]] |> matrix (ncol = 5 , byrow = TRUE ) |> as.data.frame () |> rename (name = V1, masc.mean = V2, masc.SD = V3, pos.mean = V4, pos.SD = V5) |> mutate (across (masc.mean: pos.SD, as.numeric)) |> mutate (binary = 100 * abs (masc.mean - 3 ) / 2 )
name masc.mean masc.SD pos.mean pos.SD binary
1 Bad 3.18 0.48 1.59 0.61 9.0
2 Bossy 2.50 0.77 1.98 0.61 25.0
3 Brainy 2.96 0.45 4.12 0.71 2.0
4 Brave 3.39 0.66 4.21 0.77 19.5
5 Busy 2.68 0.54 3.04 0.64 16.0
6 Chatterbox 2.19 0.63 2.71 0.84 40.5
7 Cheerful 2.87 0.44 4.56 0.60 6.5
8 Clever 2.99 0.36 4.22 0.69 0.5
9 Clumsy 3.02 0.62 2.22 0.69 1.0
10 Contrary 2.66 0.78 2.25 0.74 17.0
11 Cool 3.31 0.61 4.03 0.74 15.5
12 Curious 2.84 0.56 3.96 0.66 8.0
13 Daydream 2.67 0.62 3.18 0.92 16.5
14 Dizzy 2.38 0.58 2.45 0.71 31.0
15 Dotty 2.26 0.60 2.67 0.75 37.0
16 Fickle 2.52 0.64 1.95 0.59 24.0
17 Forgetful 2.97 0.56 2.11 0.57 1.5
18 Fun 2.95 0.37 4.57 0.64 2.5
19 Funny 3.05 0.41 4.50 0.56 2.5
20 Fussy 2.47 0.74 1.98 0.65 26.5
21 Giggles 2.03 0.56 4.25 0.72 48.5
22 Good 2.93 0.33 4.53 0.70 3.5
23 Greedy 3.31 0.53 1.64 0.65 15.5
24 Grumble 3.45 0.63 1.98 0.51 22.5
25 Grumpy 3.54 0.66 1.71 0.61 27.0
26 Happy 2.88 0.42 4.74 0.54 6.0
27 Helpful 2.65 0.49 4.47 0.60 17.5
28 Hug 2.54 0.62 4.59 0.60 23.0
29 Lazy 3.38 0.54 1.65 0.66 19.0
30 Lucky 2.98 0.36 4.10 0.73 1.0
31 Magic 2.78 0.60 4.15 0.75 11.0
32 Mean 3.02 0.55 1.46 0.63 1.0
33 Messy 3.19 0.69 2.03 0.62 9.5
34 Mischief 3.21 0.70 2.66 0.80 10.5
35 Muddle 2.86 0.46 2.31 0.63 7.0
36 Naughty 3.12 0.68 2.22 0.77 6.0
37 Neat 2.64 0.59 3.67 0.75 18.0
38 Noisy 3.18 0.63 2.29 0.70 9.0
39 Nonsense 3.05 0.47 2.22 0.78 2.5
40 Nosey 2.49 0.68 2.14 0.65 25.5
41 Perfect 2.73 0.59 4.09 1.06 13.5
42 Princess 1.32 0.55 3.13 1.13 84.0
43 Quick 2.99 0.48 3.48 0.65 0.5
44 Quiet 2.82 0.49 2.98 0.55 9.0
45 Rude 3.29 0.57 1.18 0.43 14.5
46 Rush 2.93 0.62 2.63 0.62 3.5
47 Scary 3.23 0.54 1.73 0.72 11.5
48 Scatterbrain 2.39 0.64 2.22 0.68 30.5
49 Shy 2.72 0.62 2.79 0.56 14.0
50 Silly 2.93 0.68 2.71 0.83 3.5
51 Skinny 2.51 0.64 2.73 0.80 24.5
52 Slow 3.18 0.48 2.32 0.63 9.0
53 Small 2.70 0.54 2.90 0.48 15.0
54 Splendid 2.89 0.59 4.45 0.69 5.5
55 Strong 3.52 0.74 4.13 0.67 26.0
56 Stubborn 3.08 0.69 2.12 0.71 4.0
57 Tall 3.50 0.60 3.23 0.61 25.0
58 Tidy 2.76 0.49 3.94 0.74 12.0
59 Tiny 2.39 0.61 3.06 0.57 30.5
60 Trouble 3.28 0.65 1.69 0.65 14.0
61 Uppity 2.78 0.71 1.83 0.69 11.0
62 Wise 3.09 0.58 4.40 0.60 4.5
63 Worry 2.68 0.56 2.02 0.65 16.0
64 Wrong 3.11 0.44 1.78 0.70 5.5
Plot:
%>% ggplot (aes (x = reorder (name, desc (binary)), y = binary)) + geom_point (size = 2 , aes ()) + coord_flip () + labs (x = NULL , y = "Name binariness (%)" ,title = "Little Miss and Mr Men name binariness" ) + theme (legend.position = "none" ) + theme_minimal ()
