# Values That Are Explicitly Present in Fairy Tales:
Comparing Samples from German, Italian and Portuguese Traditions

Alba Morollon Diaz-Faes
Institute for the Study of
Literature and Tradition
NOVA University of Lisbon
1069-061 Lisbon, Portugal
<EMAIL_ADDRESS>
Carla Sofia Ribeiro Murteira
Institute for the Study of
Literature and Tradition
NOVA University of Lisbon
1069-061 Lisbon, Portugal
School of Communication
and Media Studies, IPL
1549-014 Lisbon, Portugal
<EMAIL_ADDRESS>

Martin Ruskov
Department of
Languages, Literatures,
Communications and Mediations
University of Milan
20123 Milan, Italy
<EMAIL_ADDRESS>

###### Abstract

Looking at how social values are represented in fairy tales can give insights
about the variations in communication of values across cultures. We propose to
study how values are communicated in fairy tales from Portugal, Italy and
Germany using a technique called word embedding with a compass to quantify
vocabulary differences and commonalities. We study how these three national
traditions of fairy tales differ in their explicit references to values. To do
this, we specify a list of value-charged tokens, consider their word stems and
analyse the distance between these in a bespoke pre-trained Word2Vec model. We
triangulate and critically discuss the validity of the resulting hypotheses
emerging from this quantitative model. Our claim is that this is a reusable
and reproducible method for the study of the values explicitly referenced in
historical corpora. Finally, our preliminary findings hint at a shared
cultural understanding and the expression of values such as Benevolence,
Conformity, and Universalism across European societies, suggesting the
existence of a pan-European cultural memory.

##  1 Introduction

Culture is defined “as a common heritage of a set of beliefs, norms, and
values” US DHHS (2001), that influences an individual’s cognition and
behaviour Wong (2013). Social values are understood as standards or criteria
of the desirable, thus they guide the selection or evaluation of behaviours,
policies, people, and events Schwartz et al. (2020). Building on this
understanding of values as a cornerstone of culture, we turn to literature as
a mirror reflecting these values across different cultural contexts in the
past. Developments in natural language processing (NLP), in particular word
embeddings, have allowed for the quantitative analysis of historical corpora
Miaschi and Dell’Orletta (2020); Rodriguez and Spirling (2022).

With this work we want to test the limits of an approach for studying the
social values present in fairy tales, one of the most widely spread forms of
popular narratives and a privileged genre for the identification of patterns
of cultural exchange, as they have historically migrated across different
cultures and periods, creating a rich tapestry of storytelling traditions. In
particular, we study the aggregated explicit tokens mapped on the values
proposed by the Theory of Basic Human Values Schwartz (1992, 2012) across
fairy tale corpora from the traditions of three European countries – namely
Portugal, Italy and Germany – in order to compare the quantitative
representations and analyse the emerging patterns. We do this by first finding
the stemmed matches of these tokens and enriching the text with the
corresponding annotation. After that we employ a word embedding with a compass
Di Carlo et al. (2019) and clique percolations Palla et al. (2005) to
highlight the semantic variation between the three national corpora.

A critical investigation of the results of our method finds that these
correspond to findings of previous research. We also find indications that,
despite the differences on the expression of values in the three compared
countries, it seems that the values of Benevolence (quality of interpersonal
relationships), Conformity (respect for social norms and expectations) and
Universalism (protection of the welfare of people and nature) have remained
consistent in fairy tales across the three national traditions, which we also
view as confirmation of the validity of our approach for the study of values
embedded in historical, literary corpora.

This paper continues with a background section, introducing key concepts from
psychology, literary studies and NLP, and discussing relevant literature from
these fields. In Section 3, we present our approach and the software tools we
used. We provide an overview of our results in Section 4. In the final section
we conduct a discussion of the approach and results, and reflect on possible
directions for future work.

##  2 Background

The study of explicit references of values in fairy tales is related to the
accumulated social attitudes up to the historical period of codification of
the tales. To our knowledge, no systematic research of this wide topic exists.
As such, we view it as being at the crossroads between the socio-historical,
literary study of fairy tales, and the psychological study of social values
which is shaped by contemporary research. On the other hand, such a study at
scale would not be possible without the instruments and methods of
computational humanities and word embeddings in particular.

###  2.1 Unpacking Fairy-Tale Studies from the Brothers Grimm to Digital
Humanities

The late 18th century witnessed the rise of folklore studies as part of a
quest for national and cultural identity, particularly in Europe Schacker
(2003). Jakob and Wilhelm Grimm, riding the tide of renewed interest in
popular culture among the upper-class intelligentsia, became pivotal figures
in this domain. They first published their fairy-tale collection Children’s
and Household Tales in 1812, striving to present a pure German narrative
tradition, untouched by foreign influence, particularly the French Teverson
(2013). This publication sparked what would become the 19th century’s golden
age of fairy tales across Europe. This was a time of growing urbanisation,
industrialization, and literacy. Scholars and nationalists, fearful of losing
invaluable oral traditions due to these rapid societal changes, began the
collection and preservation of folklore Ostry (2013). Among these custodians
were collectors and writers such as Italy’s Giuseppe Pitré and Portugal’s
Consiglieri Pedroso, whose texts feature prominently here alongside the
Grimms’. Their work, heavily inspired by the Grimms, was driven by a desire to
distil and dialectically construct their nations’ cultural legacy.

Despite the nationalistic intentions of Brothers Grimm and others who embarked
on preserving what they thought to be distinct national narratives, the study
of fairy tales reveals as much about the interconnectedness of cultures as it
does about their uniqueness. Fairy tales, at their core, are a blend of
narratives that “migrate on soft feet” Warner and Warner (2016), indicating
that they traverse and interweave across generic, geographical and temporal
boundaries, sometimes in untraceable ways. Thus, while the Grimms and others
sought to capture and enshrine a uniquely national heritage, their work also
serves to underscore the similarities between narrative traditions.

Unpicking these similarities and differences, however, can prove to be quite a
complex task. As scholars are frequently dependent on translations, the
potential for misinterpretation or loss of nuanced meanings during this
process is high. Translations, like the ones by Margaret Hunt, Thomas Crane
and Henriqueta Monteiro used here, are enormously valuable artefacts, but must
be recognised as acts of literary adaptation that might differ from the
originals Haase (2016). These translations may introduce variations in the
representation and interpretation of values, underscoring the need for careful
consideration of linguistic nuances in cross-cultural analysis. Further
complicating matters, the comparative analysis of several national traditions
involves processing vast quantities of text to identify patterns. This
challenge extends beyond the study of fairy tales and into the comparative
study of literature as a whole.

In response to these challenges, digital humanities and computer-assisted
literary studies offer innovative methodologies. Computational methods, in
particular, aid in identifying and assessing literary patterns across scales,
from individual texts to entire fields and systems of cultural production
Wilkens (2015). These new approaches, to which our work is a contribution,
help produce new types of evidence that enrich and expand humanities research.
Indeed, computational approaches to fairy tales have already successfully been
deployed in studies such as “Computational analysis of the body in European
fairy tales” Weingart and Jorgensen (2013). In this study, the authors used
digital humanities research methods to analyse the representations of gendered
bodies in European fairy tales. They created a manually curated database
listing every reference to a body or body part in a selection of 233 fairy
tales, and its analysis revealed that the gender and age of fairy-tale
protagonists correlate in ways that indicate societal biases, particularly
against the ageing female body. A further exploration of gender bias in fairy
tales is presented in “Are Fairy Tales Fair?” Isaza et al. (2023). This study
employs computational analysis to dissect the sequence of events in fairy
tales, revealing that one in four event types exhibit gender bias when not
considering temporal order, and that female characters are more likely to
experience gender-biased events at the start of their narrative arcs. These
studies underscore the potential of distant reading, data analysis and
visualisation as powerful tools in the comparative study of fairy tales,
particularly when used alongside subject expert close reading Moretti (2022).
Nevertheless, perceptions and attitudes towards gender represent just a
fraction of the broader societal values spectrum.

###  2.2 The expression of values across cultures in European Fairy Tales

Values are regarded as a shared societal understanding of what constitutes
good, wrong, fair, unfair, just, right or ethical behaviour Haidt (2013);
Kesebir and Haidt (2010); Turiel (2005). Values are cognitive representations
of an individual’s biological needs, an individual’s requirements in
interpersonal coordination, and the institutional demands focused on group
welfare and survival Schwartz and Bilsky (1987). Nonetheless, it is crucial to
acknowledge the significance of cultural and individual influence in the
development and expression of values. Cultural Psychology postulates that
human behaviours result from the reciprocal interaction between cultural and
individual psyche Shweder (1991); Cohen (2011); Schwartz et al. (2020).
However, the manifestation of behaviors and values is contingent upon context
and situation, implying that similar cultural processes might serve or
facilitate different purposes based on cultural context Rogoff (2003);
Schwartz et al. (2020). Therefore, one could examine variations in the
expression of values across different regions and periods through the analysis
of historical corpora. This stems from the expectation that literature can be
used as a vehicle for the expression of cultural norms and values, thereby
reflecting the distinct ideological attributes of the writers and the regions
from which it emerges Albrecht (1956). Several Theories have been proposed to
summarise values across different cultures (for a review of theories see
Ellemers et al (2019)). In this paper we focus on the Theory of Basic Human
Values Schwartz (2012), since it found validity expression across several
cultures Spini (2003); Schwartz et al. (2001, 2014); Davidov et al. (2008),
and it has been applied in the study of European values (e.g., European Social
Survey). An early simpler version of the Theory of Basic Human Values Schwartz
(2012) comprises 10 human values that are fuelled by four different and
opposite motivations: Openness to Change vs. Conservation, Self-Transcendence
vs. Self-Enhancement as observed in Figure 1.

Figure 1: Theoretical model of relations among ten motivational types of
values Schwartz (2012).

Openness to Change relates to an individual’s need for independence of
thought, action, and feelings, and readiness for change, therefore comprises
the values of Self-direction, Stimulation, and partly Hedonism. On the other
hand, Conservation relates to the values of Security, Conformity and
Tradition, as it emphasises the individual’s needs for order, preservation of
the past, and resistance to change. Self-enhancement considers the
individual’s needs to pursue their own interests, success, and dominance over
others, therefore comprises the values of Power, Achievement, and partly
Hedonism. On the other hand, Self-transcendence considers the values of
Universalism and Benevolence, to focus on the welfare and better interests of
others. For a definition of specific values, see Table 1.

Table 1: The definition of each of the ten motivational types of values Schwartz (2012). Value |  Definition
---|---
Security |  Safety, harmony, and stability of society, of relationships, and of self.
Tradition |  Respect, commitment, and acceptance of the customs and ideas that traditional culture or religion provide the self. Maintaining and preserving cultural, family or religious traditions.
Conformity |  Restraint of actions, inclinations, and impulses likely to upset or harm others and violate social expectations or norms.
Self-Direction |  Independent thought and action-choosing, creating, exploring.
Stimulation |  Excitement, novelty, and challenge in life.
Hedonism |  Pleasure and sensuous gratification for oneself.
Achievement |  Personal success through demonstrating competence according to social standards.
Power |  Social status and prestige, control or dominance over people and resources.
Benevolence |  Preservation and enhancement of the welfare of people with whom one is in frequent personal contact.
Universalism |  Understanding, appreciation, tolerance, and protection of the welfare of all people and of nature.

Europeans can be regarded as having a common identity Castano (2004) that is
expressed through their way of life, values and culture, and that has been
building since ancient times Pagden (2002); Pinheiro et al. (2012) leading to
the establishment of a broad set of European Values. Values such as human
dignity, freedom, democracy, equality, rule of law, and human rights have been
declared as the values of the European Union, to form “a society in which
inclusion, tolerance, justice, solidarity and non-discrimination prevail” EU,
(2020). Based on several empirical studies and policy making guidelines, these
values correspond to Schwartz’s values of Universalism, Self-Direction, and
Benevolence (for more information see: Scharfbillig et al. (2021); Murteira
(2024). If these values are presumed to have been shared to some degree across
the European territory since antiquity, it stands to reason that they could
have been variously conveyed through fairy tales across the three regions
under analysis.

Constructs such as values can either be assessed by explicit or implicit
measures. A psychological construct is implicitly assessed when the individual
“is unaware that a psychological measurement is taking place, this type of
measure is often used to assess values, attitudes, stereotypes, and emotions
in social cognition research” APA, (2023). On the other hand, a psychological
construct is explicitly assessed when the “individual is aware that a
psychological measurement is taking place” APA, (2023). Putting it simply,
values can be measured explicitly when individuals are directly asked about
values, and implicitly when the individuals are not aware of the measurement,
because values are assessed using indirect questioning methods. Bearing in
mind that art is a behavioural expression of culture that serves several
purposes, including the form of order, which is the need for psychological and
mental organisation of experiences Dissanayake (1980), we can hold the
reasonable expectation that the historical corpora under analysis will
reflect, to a degree, the explicit and implicit cultural ways and behaviours
of societies in which these fairy tales were written. The presence of these
values in our corpora was assessed by vocabulary quantification techniques
through the development of Word Embeddings that communicate values in fairy
tales.

One particular type of explicit reference to values, are negative ones, most
trivially exemplfied by “not loving ” or “step mother”. However, this notion
of opposites to values expands into value dichotomies. These are pairs of
values that are mutually opposed, such as “deceptiveness vs. honesty” or
“trust vs. distrust”. Generally, the alternatives in a duality do not
necessarily imply a positive vs. negative interpretation, namely none of the
options is unequivocally preferable, such as “tradition vs. innovation”,
“individualism vs. collectivism”, “lawfulness vs. autonomy” Hardy (2022);
Giouvanopoulou et al. (2023). Yet, in the cases when it is a matter of a
unambiguously positive value and it’s negation, such as “love vs. hate” or
“honesty vs. dishonesty”, we argue that the negation of a value is a form of
indirect, albeit still explicit, reference to the value itself. Even more, in
some cases the two sides of the dichotomy share the same morphological origin.
Thus, we argue, that an attempt to capture explicit references to values, also
needs to capture negative ones.

###  2.3 Using Word Embeddings to Quantify Vocabulary Differences

Word embeddings have emerged as an important instrument for the quantitative
analysis of textual corpora. These are mappings of vocabulary onto a
multidimensional numerical space, based on their occurrences Mikolov et al.
(2013); Rodriguez and Spirling (2022). Different techniques for creating word
embeddings exist, but their common general principle is “a word is
characterised by the company it keeps”. It is useful to distinguish between
two categories of word embeddings: i) static (also called type-based) - those
that feature a single quantitative representation for a word token, and ii)
contextual (also called token-based) - those that allow for multiple
representations for a word token in order to capture potential nuances in
meanings, according to the surrounding context Miaschi and Dell’Orletta
(2020); Lenci et al. (2022). Whereas contextual word embeddings better capture
the richness of vocabulary, static word embeddings perform better on smaller
corpora which do not have the volume that would allow for the semantic
richness necessary to represent potential multiple meanings Ehrmanntraut et
al. (2021). Arguably, this is due to the fact that in a small thematic corpus,
typically meanings are restricted by the context of its compilation.

A widespread approach that allows to overcome the challenge of small corpora
and their lack of richness, is the combination of pre-training with a huge
generic corpus and the subsequent fine-tuning with the corpus of interest. For
example, the most popular contextual language model BERT is trained on a
corpus that includes the entire contents of Wikipedia which comprises of 2.5
billion word tokens Devlin et al. (2019), others use training sets that are
many orders of magnitude larger Dodge et al. (2021) However, corpora of these
huge dimensions are inevitably contemporarily written, and due to cultural and
linguistic change over time inevitably introduce unwanted biases de Vassimon
Manela et al. (2021); Ahn and Oh (2021); Mozafari et al. (2020); Cuscito et
al. (2024). In confirmation of this consideration, in the context of
Historical English in particular, Manjavacas and Fonteyn (2022) observed that
training from the ground up is more effective than fine-tuning of preexisting
models, and this has been independently confirmed by Cuscito et al (2024).

When it comes to comparing the word embeddings representing different corpora,
a widespread approach is the so-called semantic change detection Tahmasebi et
al. (2021). Since for intercultural comparison, “change” might wrongly suggest
a (diachronic) transition from one culture to the other, when comparing
contexts that are not sequential, a more appropriate wording in this context
is (synchronic) “semantic variation” Tahmasebi et al. (2021); Schlechtweg et
al. (2019). Still, whenever techniques for semantic change detection do not
rely on any particular diachronic properties of the underlying corpora, we
claim they could be reused also for synchronic linguistic analysis. More
specifically we claim that an approach called temporal word embedding with a
compass Di Carlo et al. (2019) is applicable, for culture-specific rather than
time-specific distinctive corpora. This approach consists of first creating an
embedding on a cumulative corpus containing all texts from the different
cultures to be considered. Then, from this baseline (compass) word embedding,
further fine-tuning is performed on each of the corpora, to be compared so as
to create culture-specific word embeddings. The result is a different
(numerical) vector representations of each particular word token, which allows
for quantitative comparisons between them, as done previously Ferrara et al.
(2022); Di Carlo et al. (2019).

##  3 Method

To describe our method, we focus first on the followed process, and then on
the tools that were used within this process.

###  3.1 Process

Our study of the explicit references to values in fairy tales follows the
process illustrated in Figure 2. To provide an outline, it starts with the
identification of tokens that represent values of interest. We group these
tokens in groups that we consider to be synonyms. Then, we automatically
annotate all occurrences in the text of the stems representing the considered
tokens. Once this is done, we manually analyse the produced annotations to
identify ambiguities and mistakes in our identification of tokens. The purpose
of this analysis is to better understand the semantics behind their
occurrences, in order to refine the selection of tokens and identify potential
tokens representing multiple values. Finally, we apply a static word embedding
with a compass and perform critical analysis on the differences from the
resulting vector spaces.

Fairy Tale Corpora GermanyItalyPortugalSelectionof TokensAutomatic
Annotationwith a StemmerWord Embeddingwith a CompassComparison ofSemantic
VariationHistorical and SocialCritical AnalysisCriticalReviewStemmedAnnotated

Figure 2: The outline of the process we followed. Table 2: Quantitative descriptors of the corpora. When we refer to tokens, we mean the ones that were identified by our automated annotation process. Complete list of included texts is available in Table 3 in Appendix. Corpus | Texts | Symbols | Words | Tokens
---|---|---|---|---
Germany (1884) | 30 | 306 475 | 59 500 | 1840
Italy (1885) | 30 | 234 158 | 45 223 | 1808
Portugal (1882) | 30 | 231 149 | 44 887 | 1439

#### Fairy Tales Corpora.

The corpus selection had several stages. First we focused on the Grimms’
Children’s and Household Tales, using Margaret Hunt’s 1884 English
translation. We manually selected 30 tales that span well-known and beloved
stories and lesser known ones, so as to provide a comprehensive representation
of the entire collection. Then we selected 30 Portuguese and 30 Italian tales
taken from two important contemporary collections to the Grimms’: Portuguese
Folktales by Consiglieri Pedroso, translated to English in 1882 by Henriqueta
Monteiro; and Italian Popular Tales, collected and translated to English in
1885 by Thomas Frederick Crane. These collections were chosen due to their
cultural significance and their temporal proximity to the Grimms’ collection,
aiming to offer a comparative perspective on 19th century fairy tales across
different European cultures.

#### Selection of Tokens.

Assuming that the historical corpora are themselves mirrors of social
behaviours and ways of living in societies in which the fairy tales were
written, we are interested in the explicit expressions of values in the texts.
Starting from Schwartz’s model and the European core values, we initially
compose a list of tokens that represent these values, based on three empirical
studies regarding value-specific tokens. This list of tokens contains words
that were selected from two dictionary studies about values, where each word
is associated with a specific Schwartz’s value. Schwartz (1992); Lindeman and
Verkasalo (2005); Murteira (2024). For instance, the token “Peace” is
associated with the value of Universalism, and the token “Cooperation” is
associated with the value of Benevolence (see Table 4 in Appendix). Then we
perform automatic identification of explicit references of values. We do this
using stemming Jabbar et al. (2020) on both the token lists and the fairy tale
texts. This is because, in contrast e.g. to lemmatisation, stemming reduces
different word forms the same originating token. We use the Snowball stemmer
algorithm Porter (2001) to identify all occurrences of the stemmed tokens in
the corpora and tag (i.e. annotate) them with a label corresponding to the
group of synonym tokens.

#### Critical Review.

We then critically analyse and refine by adapting tokens according to the
desired annotation. This was done using a specifically developed for the
purpose web interface that allows for a review of the texts in the corpora
with the results of the automatic annotation highlighted in different colours.
The tool is discussed in more details in Section 3.2. The outcome of this was
a series of decisions to adapt the token selection as a way to refine it and
guide subsequent iterations of this annotation process. Correspondingly,
following this approach inspired by grounded theory Rieger (2019), the
ultimately proposed list of tokens in this study emerges from exploration of
the corpus and is not a result of deductive hypothesis research. We provide a
statistical overview of the results of this annotation process in Table 2 and
in Appendix we provide both the complete final version of our tokens and a
Venn diagram of the occurrences of groups of synonym token across the three
corpora.

#### Word Embedding with a Compass.

Due to the historical nature of the corpora we study and in order to avoid
contaminating them with external biases from pre-training, we organise our
analysis following the word embedding with a compass approach Di Carlo et al.
(2019). To do this, we create one generic culture-agnostic shared embedding
from scratch containing all three corpora. Then, starting from this compass,
we independently create three parallel fine-tunings for each of the cultures.
For the creation of the compass, to avoid the possible introduction of biases,
we chose not to include any further possible texts, neither from any of our
three contexts, nor from others. Our approach to syntactic identification of
references to values, is not contextual, i.e. we treat a reference to a value-
related stemmed token as the same for all its identified uses. In our critical
review step we examine the validity of this generalisation. To represent the
annotations in the word embedding algorithm, before and after each identified
occurrence of a token we insert an indication of the corresponding group of
synonym tokens (i.e. the first token in it).

#### Comparison of Semantic Variation.

The word embedding allows measuring contextual similarity between words, thus
speaking of “change” and “variation”. Once we have the three word embeddings
for the cultural corpora, for each of them we consider only the distances
between groups of tokens (represented by the annotation label, i.e. the first
token in each synonym group) and experimentally define a similarity threshold
above which we consider a pair of tokens to have a relating edge between them
in a graph representation of tokens) in order to use clique percolations
clustering with k=2 Palla et al. (2005). In other words, for all similarities
above that threshold we consider the corresponding tokens to be related in
that embedding, and distances above the threshold mean the corresponding
tokens are not. This results in a clustering that might assign one token to
multiple clusters. It might also bring two tokens into the same cluster even
if the distance between them is greater than the threshold, as long as there
is a “bridge” of other tokens in between to connect them.

#### Historical and Social Critical Analysis.

At the end of our method we analyse the quantitative results using critical
analysis from the perspectives of both literary studies and psychological
research. This allows us to cross-validate (e.g. through triangulation Noble
and Heale (2019)) our results with the established body of research and thus
get an indication of their theoretical validity.

###  3.2 Automated Annotation Tool

To facilitate the critical analysis of the annotations, we developed a bespoke
tool – named moreever111Accessible online at https://tales.ko64eto.com – that
automatically identifies the explicit references to values, highlights them
for critical human review of the tales and annotations, and provides some
simple visualisation techniques to ease the comparative analysis. The main
view of the annotation tool is provided in Figure 3.

Figure 3: Screenshot of a browsing page from the bespoke web instrument that
reviews the produced annotations. Another view shows a clickable heatmap as
Figure 5 in Appendix, which allows for a distant reading view.

Both texts titles on the left and tokens on the right are clickable, which
allows easy browsing per corpus a per individual fairy tale, as well as per
value token. Through a dropdown box visible in its upper left corner of Figure
3, the tool features a list of vocabulary reduction techniques that can be
changed at runtime to allow users to examine in context throughout the corpora
texts which vocabulary reduction best approximates the generalisation of
values they are aiming for. Among these simplification techniques are
lemmatisation, as well as Porter Porter (2006), Snowball Porter (2001) and
Lancaster Paice (1990) stemmers222See implementations by
https://www.nltk.org/api/nltk.stem.html. The tool further supports no
reduction (i.e. identification only of the exact matching words) and repeated
application of Snowball stemmer for experimental.

On top of these exploratory features, moreever provides basic functionalities
for visual analysis in the form of heatmap and Venn diagrams. Heatmaps, as
shown in Figure 5 provide a bird’s-eye view of the occurrences of tokens in
tales. The featured 3-set Venn diagrams provide an overview of the occurences
of tokens across the three national corpora, as seen in Figure 4. Both
visualisations are dependent on the choice of vocabulary reduction technique,
and the provided examples are derived for the Snowball stemmer.

Germanygentl,honest,justic,pieti,pious,prizePortugalevid,knowledgItalycorrect,hospit,pureangel,claim,clever,convers,honour,judg,virginfaith,free,sacrific,support,trial,wiseaccept,gracious,harmoni,law,permiss,saintabl,brother,compass,confid,curios,curious,equal,fair,father,god,good,help,husband,innoc,jewel,just,kind,king,know,liberti,love,marri,marriag,mother,pay,peac,piti,pray,punish,queen,reason,reward,right,sister,togeth,treasur,truth,wed,wife

Figure 4: A Venn diagram showing the occurrences of tokens across the national
corpora. Figure 5: Counts of identified occurrences of tokens across the texts
of the three corpora. An interactive version of this heatmap is available at
https://tales.ko64eto.com. In it clicking on a number takes you to the
corresponding text for easier review.

##  4 Results

Figure 6: Frequencies of identified occurrences of tokens across the three
corpora. A more detailed heatmap between texts and labels is available on
Figure 5 in Appendix.

An important part of the results of our approach is the reflective inspection
of the produced automated annotation and possible corrections for these. An
overall conclusion of this process is that, expectedly, the most impactful
tokens capture the values they were intended to match well. The most important
token that did not correspond to our initial interpretation was “faith”. We
originally ascribed the label “faith” to the value of “piety,” indicating
religious devotion. However, a careful examination of our corpus revealed an
intriguing trend. The term “faith,” contrary to our initial classification,
typically expressed affiliation with “loyalty,” mainly as per the usage
patterns in various Grimm tales, particularly in “Faithful Johannes” (a German
tale). As a consequence, we ascribe the token “faith” to the value associated
to “loyalty”.

Another token that provides an interesting example is “father,” due to its
potential multiple associations. On the one hand, it could represent “caring,”
similar to “mother,” but on the other, it could be a symbol of authority Hopp
et al. (2021). When exploring the corpora, we found that “father” was
predominantly associated with “caring,” with a remarkable exception in “The
Maiden and the Fish” (Portugal), where one out of four instances appeared
associated with authoritative power.

A third, less impactful token we considered was “patient,” which was initially
associated with “kindness.” However, an analysis of the corpus found that its
usage related exclusively to an individual receiving medical treatment, and we
consequently excluded it from our analysis.

Figure 6 shows the references to values by countries, according to the
ascribed tokens. A more detailed mapping of occurrences of tokens in
particular texts is provided in Figure 5 in the Appendix. From the resulting
comparison of clusters across corpora, noteworthy is the one defined around
tokens related to “mother.” As the Venn diagram on Figure 7 shows, while in
our German and Portuguese corpora it appears together with “brother”, in the
Italian and Portuguese corpora it also appears in relation to “know.” Only in
Germany does it relate to “generous.”

GermanygenerosPortugalItalybrotherknowmother

Figure 7: An illustration of the degree of overlap across the three national
corpora for the token “mother”

###  4.1 Historical Analysis

Dolores Buttry elucidates on the usage of “faith” in Grimm tales to
exclusively mean “loyalty,” and not “piety.” She writes that the related
values of faithfulness and loyalty (which are “Treu” and “Treue” in German)
have been foundational virtues in Germany since ancient times Buttry (2011).
Stories such as “Faithful Johannes,” but also “The Frog King,” exemplify
extreme loyalty towards superiors, illustrating the importance of fidelity and
respect for authority in their various manifestations. Buttry characterises
the tale of the faithful/loyal servant as an enduring archetype, highlighting
the recurring appearance of the words “Treu” (faithful) and “Treue” (loyalty,
fidelity) in German tales Buttry (2011). She further suggests that, while
respect for authority and the sanctity of oaths were nearly universal concepts
before these stories were collected, they seem to have retained their vitality
and cultural significance particularly in German-speaking traditions. This
idea finds further support in one of the only non-German occurrences of
“faith” in our corpus, as the label appears in “The Story Of Catherine and Her
Fate,” a Sicilian tale first collected by Swiss-German folklorist Laura
Gozenbach.

It is also interesting to examine how values manifest in tales from different
cultural contexts. In our results, we found that values of “piety” and
“empathy” appeared clustered together in Italian and Portuguese tales, but not
in German ones. This may be explained by the different religious traditions in
all three countries, since both Italy and Portugal were majoritarily Catholic
regions at the time the tales were collected, while there was a strong
Protestant presence in the German territory. Indeed, Jack Zipes (2002) writes
that the Grimms’ tales portrayed the main values of Protestant ethics and the
bourgeois enlightenment. The heroes in their tales are predominantly concerned
with self-preservation and the acquisition of wealth, and they assist others,
including animals, only when they perceive a potential gain for themselves,
demonstrating a calculated approach to empathy and compassion. This model of
behavior, Zipes argues, exemplifies the general Protestant ethic of the time,
and so empathy, although occasionally appearing in the Grimms’ tales, is not a
dominant theme Zipes (2002). We may advance the possibility that the differing
religious ethos of Italy and Portugal would place more emphasis on empathy as
it relates to Catholic piety.

###  4.2 Social Analysis

Frequency analysis shows that tokens such as “mother,” “law,” brother,” and
“love” have a strong presence (more than 100 appearances) across the three
countries under analysis. Based on the elaborated correspondence between
tokens and the Theory of Basic Values (see Appendix), the words “mother,”
“brother” and “love” are connected to Benevolence, and “law” is connected to
Conformity. In Germany, the token “justice” has also a strong presence, and is
connected with the value of Universalism which stands for the protection and
welfare of all people and nature. Considering that the value Benevolence
stands for the good quality of social connections between people, and
Conformity stands for the preservation of social/cultural expectations and
norms, then we could infer that these tales describe several social dynamics.
The tales’ plots are representative of social dynamics among fictional
characters that may resemble society, in order to describe the quality of
human relationships and social/cultural norms in place.

Interestingly, some differences across countries are expressed by the tokens’
frequency related to Benevolence, Conformity and Universalism. For instance,
in Germany, “mother” seems to be a stronger reference for communication of
Benevolence than “brother” when compared to Portugal and Italy. Also, “love”
seems to be a stronger reference for communication of Benevolence in Italy
than in Germany and Portugal. However, in Germany, we may note that tokens
such as “generous” and “cooperation” reinforce the communication and
expression of Benevolence in those tales. When it concerns the need for rules
and social welfare, it seems that in Germany and Italy the token “law” is
frequently used when compared to Portugal to express the value of Conformity.
Finally, Germany shows a strong presence of token “justice” in their tales,
which highlights the importance of Universalism in these tales and the need to
convey the respect for human rights and dignity. In sum, while Portugal, Italy
and Germany communicate strongly the values of Benevolence and Conformity, it
seems that Germany also communicates the value of Universalism. Despite the
differences between countries, it seems that European Values of Benevolence
and Universalism are being communicated by the tales across countries.

##  5 Discussion and Conclusion

While the proposed approach is still in its infancy, and the emerging results
would require more thorough examination, our preliminary analysis provides
some concrete evidence that European Values have been a long-standing element
in European cultural communication through fairy tales. The corpus analysis
across different cultures revealed a significant variety in the representation
of values. For example, the affiliation of the token ”faith” with ”loyalty”
rather than ”piety,” particularly in German culture, illustrates the role of
cultural and historical contexts in shaping value representations. Similarly,
the differential clustering of ”piety” and ”empathy” in Italian and Portuguese
tales compared to German tales further underscores the influence of religious
and socio-cultural contexts in value representation. Interestingly, despite
these differences, the analysis revealed a strong commonality across all three
cultures, pointing at the communication of European Values through tales.
Tokens associated with Benevolence, Conformity, and Universalism manifested
frequently across fairy tales of all three countries. This finding is
particularly noteworthy because it suggests a shared cultural understanding
and expression of these values across European literary production, and,
possibly and by extension, across European societies, thus hinting at the
existence of a pan-European cultural memory.

We have identified clear limitations in our approach. Working at the syntactic
level, both in terms of stemming and static word embeddings, limits the
possibility to capture nuances, and with this some noise is introduced in the
analysis. However, contrary to our expectations, our detailed analysis
revealed that ambiguities are only isolated cases. This is valid to the extent
that in none of these cases a token bore semantic ambiguity that was a
dichotomy rather than an outlier so that it could undermine the general
results.

The focus on explicit references, unsurprisingly, resulted in an inability to
annotate tokens such as “democracy” in the tales, as they were only implicitly
referenced. Contextual language models are also able to capture indirect
relatedness of from the context Montanelli and Periti (2023). This has also
been attempted in the context of values, notably in the ValueEval competition
Kiesel et al. (2023); Ferrara et al. (2023); Papadopoulos et al. (2023).
However, such approaches are undermined by the variance of value perceptions
among humans. Efforts to annotate values for a ground truth chronically suffer
from appalling agreement rates. In particular, when employing an even number
of annotators, Hoover and colleagues report ties (disagreement) above 60%
across more than 6000 tweets Hoover et al. (2020). When annotating arguments
for values, Kiesel and colleagues report agreement with Krippendorff’s
$\alpha$ of 0.49 Kiesel et al. (2022), which is well below the 0.667 that
Krippendorff calls “the lowest conceivable limit” Krippendorff (2004).
Furthermore, when using contextual word embeddings we believe attention should
be paid to the possibility that the pre-trained embeddings may introduce
biases unrelated to the corpus under study.

This work provides a foundational understanding of how European Values are
represented in literary texts and highlights the potential of computational
linguistics in cultural studies. This study encourages further
interdisciplinary research in the field of literary studies, cultural
analytics, and computational linguistics to expand our understanding of
cultural values and their historical evolution.

## Acknowledgments

This project has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No 101004949. This
document reflects only the author’s view and the European Commission is not
responsible for any use that may be made of the information it contains.

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##  Appendix A Appendix

The source code of the annotation analysis tool is available at:
https://github.com/umilISLab/moreever/.

Continued with figures and tables on the following pages.

Table 3: The Fairy Tales included in the corpora. The Italian corpus includes several collectors. When not indicated, collected by Giuseppe Pitré. Otherwise, 1. Vittorio Imbriani; 2. Domenico Comparetti; 3. Laura Gozenbach; and 4. Carolina Coronedi-Berti. Germany Grimm et al. (1884) |  Italy Crane (2017) |  Portugal Consiglieri Pedroso (1882)
---|---|---
• Allerleirauh • Briar Rose • Cinderella • Faithful John • Fitcher’s Bird • Frau Trude • Godfather Death • Hansel And Grethel • King Thrushbeard • Little Red Cap • Little Snow White • Old Sultan • One Eye Two Eyes And Three Eyes • Our Lady’s Child • Rapunzel • Rumpelstiltskin • Snow White And Rose Red • Strong Hans • The Frog King Or Iron Henry • The Giant And The Tailor • The Girl Without Hands • The Jew Among Thorns • The Juniper Tree • The King Of The Golden Mountain • The Lazy Spinner • The Robber Bridegroom • The Six Servants • The Three Spinners • The Two Kings Children • The Valiant Little Tailor |  • Brother Giovannone • Cinderella3 • Don Firriulieddu • Godmother Fox • King Bean Giuseppe Bernoni • Little Chick Pea Tuscan variant • Pitidda • Snow White Fire Red • The Cat And The Mouse • The Cistern • The Cloud3 • The Crumb In The Beard3 • The Crystal Casket • The Dancing Water The Singing Apple And The Speaking Bird • The Doctor’s Apprentice • The Fair Angiola3 • The Fair Fiorita3 • The King Of Love • The King Who Wanted A Beautiful Wife3 • The Lord St Peter And The Apostles • The Parrot Which Tells Three Stories • The Sexton’s Nose • The Shepherd Who Made The King’s Daughter Laugh3 • The Stepmother • The Story Of Catherine And Her Fate3 • The Story Of Crivoliu3 • The Story Of St James Of Galicia3 • The Three Admonitions • Thirteenth • Water And Salt |  • May You Vanish Like The Wind • Pedro And The Prince • Saint Peter’s Goddaughter • The Aunts • The Baker’s Idle Son • The Cabbage Stalk • The Daughter Of The Witch • The Enchanted Maiden • The Hearth-cat • The Hind Of The Golden Apple • The Little Tick • The Maid And The Negress • The Maiden And The Beast • The Maiden And The Fish • The Maiden From Whose Head Pearls Fell On Combing Herself • The Maiden With The Rose On Her Forehead • The Prince Who Had The Head Of A Horse • The Princess Who Would Not Marry Her Father • The Rabbit • The Seven Iron Slippers • The Slices Of Fish • The Spell Bound Giant • The Spider • The Step Mother • The Three Citrons Of Love • The Three Little Blue Stones • The Three Princes And The Maiden • The Tower Of Ill Luck • The Two Children And The Witch • The Vain Queen
Table 4: List of tokens mapped with the values proposed in the Theory of Basic Values from Schwartz Schwartz (1992); Lindeman and Verkasalo (2005); Murteira (2024). Token |  Synonyms | Value
---|---|---
dialogu |  conversation | Universalism
equality |  equality, equal | Universalism
free |  free | Self-Direction
right |  right, claim | Universalism
justic |  justice, judge, trial, fairness, just | Universalism
peace |  peace | Universalism
cooper |  help, together | Benevolence
curios |  curiosity, curious | Self-Direction
empathi |  compassion, pity | Conformity
evid |  evidence | Universalism
emancip |  liberty | Self-Direction
generous |  hospitality, goodness | Benevolence
honest |  honest, confidence | Benevolence
smart |  clever, cleverness, wise | Achievement
kind |  kind, kindness, graciousness, gentleness | Conformity
know |  know, able, knowledge | Achievement
brother |  brother, sister, brotherly, sisterly | Benevolence
love |  love, married, wife, husband, marriage, wedding | Benevolence
loyal |  honor, faith | Benevolence
pieti |  piety, pious, god, virgin, saint, angel, pray | Tradition
mother |  mother, father, motherly, fatherly | Benevolence
punish |  punish, punishment | Conformity
pure |  pure, innocent, innocence | Tradition
correct |  correct, reason, correctness | Universalism
reward |  reward, prize, pay, treasure, jewels | Power
law |  lawful, king, queen | Power
solidar |  harmony, support | Benevolence
toler |  acceptance, permissiveness | Universalism
truth |  truth | Universalism