Cognitive factors explain inter-cultural variations of abilities in rhythm perception: The case of the Roma minority

Abstract

This study aimed to determine what role cognitive factors play in inter-cultural variations of rhythm perception and to assess whether the stereotype of enhanced musical abilities in the Roma minority is supported by empirical evidence. The rhythm perception of 487 Roma and non-Roma children was assessed comparatively, while controlling for cognitive skills. Contrary to popular belief, the rhythm perception of Roma children was lower than that of their non-Roma peers; however, this difference in performance was explained fully by cognitive variables. The results indicate that further comparative investigations of rhythm perception across cultures should account for cognitive factors, and that the reported enhanced musical ability of the Roma minority is a stereotype that is not supported by empirical evidence.

Keywords

Rhythm perception cultural factors cognitive factors Roma minority cross-cultural

It has been widely accepted for many decades that cognitive development relies heavily on social interactions – a claim supported by the socio-cultural theory based on Vygotsky’s work (1978). In past years, systematic empirical research has documented that one such cognitive ability, rhythm perception, can be greatly influenced by cultural factors (for a review, see Morrison & Demorest, 2009). For instance, a series of studies conducted by Hannon and Trehub (2005a, 2005b) have shown that by the time infants turn 1 year old, they are less sensitive to rhythmical patterns violations from an unfamiliar culture, and more sensitive to violations of rhythmical patterns specific to their own culture. This finding is supported by cross-cultural research, which has consistently shown that people living in different cultures develop the ability to perceive rhythm differently. For instance, Cameron, Bentley and Grahn (2015) have identified inter-cultural differences in rhythm perception between East African and North American participants, while accounting for age, gender, and mean years of musical and dance training. Hannon, Soley and Ullal (2012) have also identified inter-cultural variability in rhythm perception between participants from Turkey and the United States (US), while matching the two groups by age and gender, and accounting for reported hearing acuity and musical training. Kalender, Trehub and Schellenberg (2013) have seen significant variability in meter perception of an unfamiliar music style (Turkish) as a function of the cultural background of the participants (Western only vs. non-Western), while accounting for musical training. All of these studies suggest that rhythm perception is heavily influenced by an individual’s cultural exposure.

However, the aforementioned and other studies have surprisingly failed to account for the varying cognitive abilities of their participants, despite the fact that literature has shown that cognitive factors can significantly predict musical ability in general (Schellenberg & Weiss, 2013) and rhythm perception in particular (see below). Thus, their findings do not explain to what extent the inter-cultural differences in rhythm perception are caused by cultural factors (such as a strong musical tradition within a specific culture) or by individual cognitive abilities (such as enhanced performance of auditory discrimination). This is why conducting a cross-cultural study that compares the rhythm perception abilities of participants from two different cultures while accounting for their varying cognitive skills is paramount to explaining how much of this inter-cultural variability is determined by cultural background (and not by cognitive ability). Our study is the first to explore this aspect of cultural differences in rhythm perception.

Cognitive factors associated with rhythmic skills

Empirical evidence has indicated that rhythm perception can be significantly associated with cognitive variables, such as general intelligence, phonological awareness and working memory. For instance, studies using both behavioral and neuroimaging techniques pointed out that general intelligence (measured using Raven’s Progressive Matrices) is associated strongly with rhythm perception (Helmbold, Troche, & Rammsayer, 2007; Loras, Stensdotter, Ohberg, & Sigmundsson, 2013; Ullen, Forsman, Blom, Karbanov, & Madison, 2008). This correlation is explained by the fact that general intelligence and some of the abilities that are critical to rhythm perception (i.e. temporal stability and reaction time) share neural substrates located in the prefrontal cortex. Another variable that has been associated strongly with rhythm perception is phonological awareness, or the ability to break down speech segments into sounds (Huss, Verney, Fosker, Mead, & Goswami, 2011; Moritz, Yampolsky, Papadelis, Thompson, & Wolf, 2013). Apparently, the development of these two cognitive abilities follows similar patterns, with empirical evidence indicating that teaching rhythmical perception leads to an improvement in phonological awareness (Francois, Chobert, Besson, & Schon, 2013). Finally, another cognitive variable strongly correlated with rhythm perception is working memory (Jerde, Childs, Handy, Nagode, & Pardo, 2011; Teki & Griffiths, 2016). This ability can play an important role, particularly when participants are required to complete highly complex tasks (similar to the ones used in this study) that require them to remember patterns of multiple items. Therefore, accounting for such cognitive factors seems to be important when we conduct comparative studies that measure rhythm perception abilities across cultures. Moreover, even though each of the aforementioned cognitive variables (general intelligence, phonological awareness, and working memory) has been associated with rhythm perception separately, no study has accounted for all three factors simultaneously; the present study will be the first to do so. This is particularly useful in determining whether each of the three factors has significant predictive value, or whether a certain factor (such as general intelligence) plays a more important role or even overrides the effects of the others.

The case of the Roma minority

Roma (also known as gypsies or travelers) is an ethnic minority often cited as a group known to produce many talented musicians. Drawing their origins from northern India, the Roma emigrated to Europe in the 1400s. From there, a part of the population emigrated to the US at the end of the 1800s. Today, it is estimated that there are about 12 million Roma living in the European Union, and close to 1 million in the US (FRA, 2014; Mendizabal et al., 2012; Sutherland, 2017). Historical documentation shows that performing music was one of the oldest occupations for Roma (Gojkovic, 1986), and their authentic music (with a strong stress on rhythm) influenced several Western folk music styles (e.g. flamenco, see Pitrowska & Torr, 2013). Roma have long been thought to be very skilled musicians, as “for hundreds of years music has been a viable Romani occupation” (Silverman, 2012, p. 241) and “Roma became indispensable suppliers of diverse services to non-Roma, notably music” (Silverman, 2012, p. 8). The representation of the Roma minority as a musically talented, free-spirited and romantic people is still persistent in Western culture (Villano, Fontanella, Fontanella, & Donato, 2017), with music serving as a central element in movies depicting Roma (Andreescu & Quinn, 2014) and often referenced as part of Roma identity (Silverman, 2012). These circumstances facilitated the development of the belief that Roma are exceptionally talented musicians, whose skills are superior to non-Roma due to their musically rich cultural tradition (Currid, 2006, p. 191; Pogany, 2004, p. 67). However, to date there is no empirical evidence to support this stereotype, and the present study is the first attempt to scientifically investigate this assumption. Addressing this issue can elucidate the validity of the plausible but untested hypothesis that the development of an individual’s rhythm perception ability is heavily influenced by his or her cultural environment, even after accounting for the effects of cognitive abilities.

There is a large body of evidence indicating that the Roma minority has been struggling with poverty for centuries (FRA, 2014; O’Nions, 2016), and systematic research has shown that poverty is associated with lower cognitive abilities (Al Hazzouri et al., 2017; Hackman & Faran, 2009). Indeed, empirical studies have claimed that Roma perform significantly poorer than non-Roma in cognitive tasks that are associated with rhythm perception, such as non-verbal cognitive skills measured with Raven’s Progressive Matrices (Bakalar, 2004; Rushton, Cvorovic, & Bons, 2007) and in the area of phonological awareness (Dolean, Tincas, & Damsa, 2016). Such findings lead to another plausible (but competing) hypothesis: given their reported low socio-economic status and low cognitive abilities, the rhythm perception abilities of Roma are lower than the ones of their non-Roma peers (and a musically rich culture would not compensate for this difference in skills). This hypothesis supports the idea that Western society may have overestimated the musical abilities of Roma. This is explained by the fact that, while Roma have been persecuted and discriminated against throughout their history as an ethnic minority, at the same time, they have been appreciated as musicians, and their music has helped them highlight their distinctiveness (Maners, 2006). Thus, as music was the gateway through which Roma were accepted traditionally by the mainstream society, a stereotype that Roma are more musically talented than non-Roma was developed. To date, there are no scientific studies that have investigated either hypothesis.

Research questions

In order to test the aforementioned hypotheses, we asked two research questions:

Will Roma have better rhythm perception abilities than non-Roma? We support the second hypothesis and assume that this stereotype is not scientifically valid, given the reported poverty and low cognitive abilities of Roma.

To what extent do cognitive factors explain the potential inter-cultural variations of abilities in rhythm perception? We hypothesize that cognitive factors significantly correlate with rhythm perception and that they can play a crucial role when it comes to the potential inter-cultural variability.

Method

Participants

Five hundred children (Roma and non-Roma) from 21 participating schools in the Transylvania region of Romania were initially selected to participate in this study. The participating schools were selected for their high representation of Roma population. However, the schools were representative of the local communities in the geographical location of our study: they were all state-funded (the norm for these communities) and the enrollment was typical for the size of each participating community, with no categorization of schools or classes based on the students’ academic abilities or financial status.

The children participating in our study represented the entire school population registered in the first grade in fall 2014 for each school whose parents provided parental consent for this study. Children were aged between 6 and 9 years at the beginning of the study. The rather wide age range of our participants is explained by the fact that, while first graders in Romania are typically 7–8 years old, children are occasionally registered to school earlier (if parents and school officials consider them developmentally ready) or later (particularly in rural areas, where children do not always attend kindergarten consistently, resulting in developmental delays that adversely impacts their school readiness). We selected this age group for two reasons. One was to ensure that participants would meet the minimum age criteria for rhythmical abilities task administration and for understanding the instructions of the task in order to help researchers collect data accurately (see below details about Stambak task). The other reason we chose this age group was to ensure that participants were young enough to limit the effects of schooling on the development of the measured cognitive abilities (which could have impacted differently the two ethnical groups, given that historically, Roma children tend to attend school less frequently than their non-Roma peers).

The ethnicity of each participant was identified by demographic surveys completed by parents and collected by each school during the process of student registration in the school. The majority of participating communities were typical small town/rural communities in Romania, with little ethnic diversity; therefore, there were no fine-grained distinctions between and within the two ethnic groups.

Out of the 500 children, the data of 13 children were eliminated from the analysis because the children had previous exposure to formal musical training, which could have influenced their rhythm perception scores (Yates, Justus, Atalay, Mert, & Trehub, 2017). A further 85 children (64 Roma) missed at least one of the assessment sessions. Little’s MCAR test was marginally significant, χ²(52) = 68.37, p = .06. We hypothesized that this value might be due to the higher number of missing data present in the Roma children, and therefore repeated the same test separately for the two Ethnicity groups. We found that the data were missing completely at random in both the Roma, χ²(52) = 57.79, p = .27, and the Non-Roma group, χ²(22) = 20.53, p = .55. We therefore replaced the missing data using Multiple Imputation. Thus, the final sample consisted of 487 children aged between 6 and 9 years (250 boys; M age = 89.08 months, SD = 4.78). Out of these, 310 children (162 boys) were of Roma ethnicity (M age = 89.58 months, SD = 5.03) and 177 (88 boys) of Non-Roma ethnicity (M age = 88.19 months, SD = 4.17).

Procedures and measures

All research protocols were in compliance with the internal guidelines of the institutions of investigators. All children were assessed individually in a quiet room in the schools where they were registered. The assessment was split into three distinct sessions: one that assessed IQ, one that assessed phonological processing and working memory, and one that assessed rhythmical skills. The length of each session varied, but none lasted more than 20 min. The assessors were trained school psychologists, researchers, or elementary school teachers with a minimum of 5 years of experience working with elementary school children.

Rhythmic skills

The children’s rhythm perception was measured with the Stambak task (Stambak, 1951), a rhythm reproduction measure that requires children to repeat the rhythmic sequences they hear by tapping a pencil on the table (see also Dellatolas, Watier, LeNormand, Lubart, & Chevrie-Muller, 2009). The task has 2 practice items and 21 test items of increasing complexity. In this study, the audio items were recorded as audio files and played on the assessors’ laptops (which had standardized audio settings). The task had good internal consistency (Cronbach’s α = .86).

General intelligence

General intelligence (IQ) was measured using Raven’s color matrices scale (Raven, Raven, & Court, 1991). The responses were coded on a scale from 0 to 36. This Romanian adapted version of the scale on a nationally representative sample indicated a test-retest reliability of .67 after 6 months. The internal consistency (Cronbach’s α) computed on our data was good (.86).

Phonological awareness

The phonological awareness (PA) of children was assessed using the phonological processing subscale of NEPSY adapted and validated for the Romanian population (Korkman, Kirk, & Kemp, 1998). Children’s scores could range from 0 to 36. During this measure, children were asked to identify words from word segments and to create new words by substituting or omitting phonemes. The reported split half reliability of the scale was .93. The internal consistency score in our data (Cronbach’s α) was .86.

Working memory

The working memory (WM) was measured by a backward digit span task, in which children are required to listen to multiple series of digit sequences (e.g. 2,6,4), and then to repeat what they have heard backwards (e.g. 4,6,2). The task had four levels of difficulty, ranging from level 1 (two digits) to level 4 (five digits). Each level had six equally difficult tasks. The children’s scores could have ranged from 0 to 24. The internal consistency score in our data (Cronbach’s α) was .87.

Results

We first carried out a series of preliminary analyses to determine the extent to which children’s age or gender was related to their performance on the tasks included in this study. An independent-samples t-test indicated that Roma children were older than non-Roma children (see Table 1). Additionally, age was negatively related to WM and to a composite cognitive score of the three cognitive variables (CompCog) in the case of Roma children (see Table 2), but not in the non-Roma group. To determine the effect of gender across the two Ethnicity groups, we carried out a series of 2 (Gender) × 2 (Ethnicity) ANOVAs, with each performance score, in turn, as the dependent variable. Results indicated that Gender had no effect on children’s performance, all F values (1, 483) = 0.01–0.73, all p values = 0.39–0.91, η_p² = 0–0.002. There was also no Gender × Ethnicity interaction, all F values (1, 483) = 0.01–0.66, all p values = 0.42–0.91, η_p² = 0, indicating that the absence of gender differences manifested in both Roma and non-Roma children. We repeated the same analysis with Age as the outcome variable. This analysis revealed that girls (M = 88.59 months, SD = 4.72) were significantly younger than boys (M = 89.54 months, SD = 4.79), F(1, 483) = 5.23, p < 0.05, η_p² = .01, and that this effect was equally present in both Roma and non-Roma children (as there was no interaction effect), F < 1, ns. Because gender did not appear to play a significant role in children’s performance, we decided not to include this variable in any further analyses.

Table 1.

Descriptive statistics for each variable across ethnicity, and results of independent-samples t-tests.

	Roma	Non-Roma	t	d †
	M (SD)	M (SD)	t	d †
Age (months)	89.58 (5.03)	88.19 (4.17)	3.08*	0.30
Rhythm	8.86 (4.27)	11.21 (4.29)	−5.83**	0.55
Raven	14.69 (5.40)	20.22 (6.08)	−10.38**	0.96
PA	9.49 (4.28)	13.11 (5.98)	−7.74**	0.70
WM	4.36 (3.33)	7.34 (3.64)	−9.18**	0.85
CompCog	−0.30 (0.68)	0.49 (0.81)	−11.49**	1.05

p < 0.01, **p < 0.001, †Cohen’s d.

Table 2.

Correlations (Pearson’s r) between variables for Roma children (above the diagonal) and non-Roma children (below the diagonal).

	(1)	(2)	(3)	(4)	(5)	(6)
(1) Age (in months)	-	0.014	−0.125*	−0.048	−0.147**	−0.103
(2) Rhythm	0.023	-	0.405**	0.377**	0.307**	0.282**
(3) CompCog	−0.021	0.491**	-	0.782**	0.836**	0.774**
(4) Raven	−0.043	0.354**	0.746**	-	0.479**	0.381**
(5) WM	−0.033	0.428**	0.820**	0.477**	-	0.503**
(6) PA	0.020	0.379**	0.795**	0.330**	0.484**	-

p < 0.05, **p < 0.01.

Next, we set out to determine if there were any differences in rhythm perception between Roma and non-Roma children. An independent-samples t-test indicated that Roma children had significantly lower rhythm perception scores, t(485) = –5.82, p < .001, d = 0.55. They also scored lower than their non-Roma peers on all three cognitive variables assessed for this study (see Table 1).

Next, we correlated the rhythm perception abilities with each of the three cognitive variables (IQ, WM, PA) and with CompCog. All three cognitive variables as well as the composite score correlated significantly with rhythm perception (see Table 2). We repeated the correlation analyses controlling for age, and the results were virtually identical.

Finally, we tried to determine whether the children’s general cognitive abilities might explain the difference in the rhythm perception scores between the two groups of children. We therefore created a composite score by averaging the z-transformed scores of IQ, WM and PA (see CompCog in Table 1). Next, we carried out separate univariate ANCOVAs, where we controlled for age and one cognitive variable (including CompCog) at a time, and using Rhythm as the dependent variable, and Ethnicity as the between-groups variable. The difference between the two groups became non-significant only when controlling for the effect of CompCog F(1, 474) = 0.63, p = 0.43, η_p² = 0.001. CompCog significantly predicted Rhythm scores, F(1, 474) = 114.66, B = 2.58, SE = 0.24, p < 0.001, η_p² = 0.19. Neither IQ, F(1, 474) = 3.49, p = 0.06, η_p² = 0.01, nor WM, F(1, 474) = 6.11, p < 0.05, η_p² = 0.01, nor PA, F(1, 474) = 10.84, p < 0.01, η_p² = 0.02, seemed to explain the difference by themselves.

Discussion

Theoretical and empirical studies support the idea that the development of rhythm perception skills can be influenced by cultural factors (Morrison & Demorest, 2009), but the scientific literature has provided evidence that variation in these skills is also explained by cognitive abilities. No previous study has investigated the influence of culture on rhythm perception while accounting for cognitive factors, and the present study aimed to fill this gap. To do so, we selected to study Roma minority, who have long been perceived to have higher musical skills than their non-Roma peers, due to the high prevalence of Roma musicians in Western civilizations (Silverman, 2012) and due to the fact that music was often featured as a central element in movies depicting Roma characters (Andreescu & Quinn, 2014). Thus, the first goal of the present study was to assess the extent to which the musical abilities of Roma children differed from those of their non-Roma peers by measuring rhythm perception, one of the components of musical skills. The results indicated that Roma children from our sample did not have higher rhythm perception abilities when compared with their non-Roma peers; instead, they exhibited significantly lower rhythm perception abilities than did their non-Roma peers. Based on these findings, there is little evidence to support the hypothesis that the development of rhythm perception abilities is heavily influenced by the cultural environment, leading people from musically rich cultures (such as Roma) to have superior musical talent (Currid, 2006; Pogany, 2004). Rather, the findings support our hypothesis that Western society has overestimated the musical talent of Roma because music was traditionally used by this ethnic group as a means of displaying their distinctiveness and finding acceptance in mainstream society (Maners, 2006).

Another aim of our study was to identify to what extent cognitive variables can explain potential inter-cultural variations of abilities in rhythm perception. For this purpose, we have accounted for cognitive variables (general intelligence, phonological awareness and working memory) while comparing the rhythm perception abilities of two ethnic groups with different cultural backgrounds, and examined for the first time the association between rhythm perception and the three aforementioned cognitive variables simultaneously. The hypothesis that rhythm ability is associated with the three cognitive variables was confirmed by the results of the correlation analysis, which support previous findings (Jerde et al., 2011; Huss et al., 2011; Teki & Griffiths, 2016) and suggests that cross-cultural comparative measurements of rhythm perception should account for cognitive variables. The results of the comparative analysis of the cognitive skills of the two groups are also partially supported by previous research (Bakalar, 2004; Dolean et al., 2016; Rushton et al., 2007), which anticipated that the rhythm perception of Roma would be lower due to their lower cognitive performance. Indeed, after the composite score of the three variables was accounted for, there was no difference between the two groups, suggesting that cognitive variables play a crucial role when it comes to inter-cultural variations of abilities in rhythm perception. However, when each of the three cognitive variables was controlled individually, none of them contributed significantly enough to bridge the gap of rhythm perception abilities between the two groups, suggesting that such cultural differences are explained by a variety of cognitive factors. It was interesting, however, to note the marginal non-significant effect of intelligence, which suggests that general non-verbal abilities can have a strong influence on rhythm perception skills (Ullen et al., 2008).

The conclusions of the present study regarding the musical abilities of Roma need to be treated with caution as the measure of rhythm perception offers only a limited perspective of musical abilities. Further investigations need to be performed to account for a larger variety of musical skills (e.g. pitch discrimination or harmony). However, the results of this study suggest that further investigations that measure rhythm perception ability comparatively across cultures need to strongly consider accounting for cognitive abilities.

Footnotes

Acknowledgements

The first author would like to thank Marius Bob for his assistance with recording the rhythmic task.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by EEA grants / Norway Grants under the program “Research within priority sectors” (15 SEE/30.06.2014).

ORCID iD

Dacian Dorin Dolean

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S. E.

(2017). Effects of musical training and culture on meter perception. Psychology of Music, 45(2), 231–245.