Sagerska målet by Sophie L. Sager : Difficulty Assessment for Swedish Learners

How difficult is Sagerska målet for Swedish learners? We have performed multiple tests on its full text (freely available here) of approximately 20,505, crunched all the numbers for you and present the results below.

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Difficulty Assessment Summary

We have estimated Sagerska målet to have a difficulty score of 58. Here're its scores:

Measure Score
easy difficult (1 - 100)
Overall Difficulty 58% 58
Vocabulary Difficulty 74% 74
Grammatical Difficulty 43% 43

Vocabulary Difficulty: Breakdown

74%

Vocabulary difficulty: 74%

This score has been calculated based on frequency vocabulary (the top most frequently used words in Swedish). It combines various measures of Sagerska målet's text analyzed in terms of frequency vocabulary: a plain vocabulary score, frequency-weighted vocabulary score, banded frequency vocabulary scores based on vocabulary of the text falling in the top 1,000 or 2,000 most frequent words, etc. Here's a further breakdown of how often the top most frequently used words in Swedish appear in the full text of Sagerska målet:

Vocabulary difficulty breakdown for Sagerska målet: a test for Swedish top frequency vocabulary

We have also calculated the following approximate data on the vocabulary in Sagerska målet:

Measure Score
Measure Score
Number of words 20,505
Number of unique words 4,013
Number of recognized words for names/places/other entities 593
Number of very rare non-entity words 1,225
Number of sentences 2,394
Average number of words/sentence 9

There is some research suggesting that that you need to know about 98% of a text's vocabulary in order to be able to infer the meaning of unknown words when reading. If true, this means that you would need to know around 3,932 words (where all the forms of the word are still counted as unique words) in Swedish to be able to read Sagerska målet without a dictionary and fully understand it.

Grammatical Difficulty: Breakdown

43%

Grammatical difficulty: 43%

Here is the further grammatical comparison on this text. You can find an explanation of all these scores below.

Measure Score
Measure Score
Automated Readability Index 4
Coleman-Liau Index 7
Type/Token Ratio (TTR) 0.195708
Root type/Token Ratio (RTTR) 0.00000954442
Corrected type/Token Ratio (CTTR) 0.00000477221
MTLD Index 47
HDD Index 56
Yule's I Index 57
Lexical Diversity Index (MTLD + HD-D + Yule's I) 53

The type-token ratio (TTR) of Sagerska målet is 0.195708. The TTR is the most basic measure of lexical diversity. To calculate it, we divide the number of unique words by the number of words in the text. For example, for this text, the number of unique words is 4,013, while the number of words is 20,505, so the TTR is 4,013 / 20,505 = 0.195708. However, the TTR is a very crude measure, as it is extremely dependent on text length. The longer the text, the lower the TTR is usually going to be, since common words tend to often repeat. Especially since the number of words in this text is more than 1,000, the TTR is not likely to give an accurate measure.

The root type-token ratio (RTTR) and corrected type-token ratio (CTTR) are measures which were suggested by researchers to partially address the problem of TTR's variance on text length. In the RTTR, the number of unique words is divided by a square of the number of words (therefore, 4,013 / (20,505 * 20,505) = 0.00000954442), while in CTTR, it is divided by a square of the number of words, multiplied twice 4,013 / 2 * (20,505 * 20,505) = 0.00000477221). However, these measures are not as easily readable, and also there is a growing body of research asserting that CTTR and RTTR do not effectively address the problems of text length. Therefore, while we do provide the full text's TTR, RTTR and CTTR on this page, these fiqures do not form part of our final calculations.

The Automated Readability Index (ARI) is one readability measure that has been developed by researchers over the years. The formula for calculating the ARI is as follows:
Formula for calculating the Automated Readability Index

The ARI should compute a reading level approximately corresponding to the reader's grade level (assuming the reader undertakes formal education). Thus, for example, a value of 1 is kindergarten level, while a value of 12 or 13 is the last year of school, and 14 is a sophomore at college. The current ARI of this text is 4, making it understandable for 4-grade students at their expected level of education.

The Coleman Liau Index (CLI) is a similar index designed by Meri Coleman and T. L. Liau, and it is supposed to compute the grade level of the reader (thus, for example, sophomore level material would be around grade 14, or year 14 of formal education, while kindergarten / primary school level material would be close to grade 1 in the CLI). The CLI is usually slightly higher than the ARI. The CLI is computed with this formula:
Formula for calculating the Coleman-Liau Readability Index

It is notable that other indexes exist, such as the Flesch-Kincaid Reading Ease, Gunning-Fog Score, and others, but we have chosen not to include them, since, contrary to the ARI and CLI, such other indexes are based on a syllable count and therefore arguably only work for English and not Swedish.

We compute a further compound lexical diversity index, which should range from 1 to a 100 (with the standard deviation being around 10, and its average value being around 50) - it is 53 in the present case. The compound lexical diversity index consists of the following indexes, averaged out (and also provided in the table above):

  • the Measure of Textual Lexical Diversity (MTLD) index - a measure which is based on computing the TTR for increasingly larger parts of the text until the TTR drops below a certain threshold point (around 0.7 in our case) - in which case, the TTR is reset, and the overall counter is increased; the counter is at the end divided by the number of words in text; as a result, the MTLD does not significantly vary by text length;
  • the Yule's I index (based on Yule's K characteristic inverted) - an index based on the work of the statistician G.U. Yule, who published his index of Frequency Vocabulary in his paper "The statistical study of literary vocabulary"; Yule's I takes into account the number of words in the text, and a compound summed measure of word frequency;
  • the Hypergeometric Distribution D (HD-D) index (based on vocd) - an index which assesses the contribution of each word to the diversity of the text; to calculate such contributions, a hypergeometric distribution is used to compute probabilities of each word appearing in word samples extracted from the text; then such distributions are divided by sample sizes and added up;

Our overall measure of grammatical diversity is based on a combination of the compound lexical diversity index (which includes the MTLD, Yule's I and HD-D indexes), the ARI and CLI, all normalized and given certain weight. The score should normally range from 1 to 100. In this case, the score is 43.

Other Information about Sagerska målet by Sophie L. Sager

We provide you a sample of the text below, however, the full text of the Sagerska målet is also available free of charge on our website.

Sample of text:

Möller (den elake finne) brukade säga att jag var så barnslig, hvilket jag vill vara i det onda, men han får se nu genom min fullkomligt sanna skrift, om jag är barnslig till förståndet; och svagsint, som han sagt, men som aldrig någon hederlig menniska, hvarken haft skäl till eller kan säga, ty jag har inga dårskaper begått. På Möllers osanna, osammanhängande berättelse af hvilken man hörde ej någon var fullständig, och dem som skulle vara något på håll var så mycke vittnande om hans minneslöshet, att man skulle kunna tro, att han, i stället för jag, förlorat något af sitt ringa förstånd, då han bland annat, säger, att han sagt till mig, att han ville, att jag skulle resa tillbaka, och att jag svarat, att jag heller kastar mig i strömmen; det var osanning att det var så, såväl som alla andra hans dikter. Jag tror nog att han låtsade för kapitenen på fartyget, som ej ansåg honom för väl, att han ...

Top most frequently used words in Sagerska målet by Sophie L. Sager*

Position Word Repetitions Part of all words
Position Word Repetitions Part of all words
1 jag 731 3.56%
2 att 711 3.47%
3 och 563 2.75%
4 som 483 2.36%
5 ej 450 2.19%
6 det 405 1.98%
7 han 369 1.8%
8 mig 321 1.57%
9 en 288 1.4%
10 för 284 1.39%
11 var 234 1.14%
12 till 230 1.12%
13 hon 228 1.11%
14 204 0.99%
15 204 0.99%
16 men 191 0.93%
17 183 0.89%
18 med 180 0.88%
19 af 180 0.88%
20 är 179 0.87%
21 de 174 0.85%
22 om 169 0.82%
23 den 167 0.81%
24 sig 127 0.62%
25 min 111 0.54%
26 henne 97 0.47%
27 kan 95 0.46%
28 sade 95 0.46%
29 har 91 0.44%
30 hade 90 0.44%
31 ty 88 0.43%
32 skulle 84 0.41%
33 väl 78 0.38%
34 ville 76 0.37%
35 kunde 73 0.36%
36 honom 70 0.34%
37 dem 67 0.33%
38 Sager 66 0.32%
39 hans 65 0.32%
40 ett 64 0.31%
41 man 63 0.31%
42 vill 63 0.31%
43 der 62 0.3%
44 än 62 0.3%
45 någon 61 0.3%
46 eller 60 0.29%
47 vara 60 0.29%
48 något 57 0.28%
49 sin 55 0.27%
50 nu 52 0.25%
51 hennes 49 0.24%
52 Möller 48 0.23%
53 kom 47 0.23%
54 utan 47 0.23%
55 nog 44 0.21%
56 hvad 43 0.21%
57 varit 42 0.2%
58 mitt 42 0.2%
59 mer 42 0.2%
60 hos 42 0.2%
61 efter 42 0.2%
62 vid 40 0.2%
63 hvilket 40 0.2%
64 icke 39 0.19%
65 från 39 0.19%
66 Gud 38 0.19%
67 fick 38 0.19%
68 mycket 38 0.19%
69 allt 37 0.18%
70 alla 36 0.18%
71 35 0.17%
72 några 34 0.17%
73 göra 32 0.16%
74 andra 32 0.16%
75 här 32 0.16%
76 sa 31 0.15%
77 sjelf 30 0.15%
78 30 0.15%
79 samt 30 0.15%
80 vi 30 0.15%
81 ni 30 0.15%
82 detta 30 0.15%
83 sitt 30 0.15%
84 gick 30 0.15%
85 se 29 0.14%
86 gjorde 29 0.14%
87 sagt 29 0.14%
88 äfven 29 0.14%
89 säga 29 0.14%
90 förut 28 0.14%
91 blef 28 0.14%
92 Stockholm 27 0.13%
93 mot 27 0.13%
94 skall 27 0.13%
95 mina 26 0.13%
96 får 26 0.13%
97 gör 26 0.13%
98 säger 25 0.12%
99 såg 25 0.12%
100 genom 25 0.12%
101 fast 25 0.12%
102 ingen 25 0.12%
103 fru 24 0.12%
104 hvilken 24 0.12%
105 deras 24 0.12%
106 veta 23 0.11%
107 Dillström 23 0.11%
108 ha 23 0.11%
109 annat 23 0.11%
110 gång 23 0.11%
111 kunna 22 0.11%
112 också 22 0.11%
113 tror 22 0.11%
114 ut 22 0.11%
115 blifvit 21 0.1%
116 sina 21 0.1%
117 emot 21 0.1%
118 vet 21 0.1%
119 sedan 21 0.1%
120 blott 21 0.1%
121 otäcka 20 0.1%
122 öfver 20 0.1%
123 Möllers 20 0.1%
124 denna 20 0.1%
125 dock 20 0.1%
126 hur 19 0.09%
127 Hesselberg 19 0.09%
128 aldrig 19 0.09%
129 tänkte 19 0.09%
130 när 19 0.09%
131 in 19 0.09%
132 uti 18 0.09%
133 ändå 18 0.09%
134 äro 18 0.09%
135 många 18 0.09%
136 måste 18 0.09%
137 hustru 17 0.08%
138 såsom 17 0.08%
139 hus 17 0.08%
140 annan 17 0.08%
141 flicka 16 0.08%
142 hvarken 16 0.08%
143 bättre 16 0.08%
144 Ström 16 0.08%
145 namn 15 0.07%
146 god 15 0.07%
147 sådana 15 0.07%
148 mycke 15 0.07%
149 oss 15 0.07%
150 sanningen 15 0.07%
151 behöfver 15 0.07%
152 alltid 15 0.07%
153 tyckte 15 0.07%
154 förr 15 0.07%
155 fått 15 0.07%
156 går 14 0.07%
157 hederlig 14 0.07%
158 bli 14 0.07%
159 inte 14 0.07%
160 trodde 14 0.07%
161 ondt 14 0.07%
162 hafva 14 0.07%
163 sätt 14 0.07%
164 person 14 0.07%
165 Dillströms 14 0.07%
166 dit 14 0.07%
167 hört 14 0.07%
168 komma 14 0.07%
169 under 14 0.07%
170 taga 13 0.06%
171 snart 13 0.06%
172 hit 13 0.06%
173 sådan 13 0.06%
174 dikter 13 0.06%
175 vore 13 0.06%
176 både 13 0.06%
177 Jönköping 13 0.06%
178 1848 13 0.06%
179 sen 13 0.06%
180 låg 13 0.06%
181 ännu 13 0.06%
182 fl 13 0.06%
183 ord 13 0.06%
184 rätt 12 0.06%
185 berättelse 12 0.06%
186 bo 12 0.06%
187 bostad 12 0.06%
188 kanske 12 0.06%

This list excludes punctuation or single-letter words, also some different-case repeats of the same words.

If you think the text would be accessible to you, you can read it on our site (click on the cover to access):

Cover of Sagerska målet by Sophie L. Sager

Other resources and languages

If you like this analysis, you should have a look at out our lists of Swedish short stories and Swedish books.

If you like literature as a means to learn languages - please take a look at our project Interlinear Books. We even have a Swedish Interlinear book available for purchase.