First Monday

Conceptualizing the techno-environmental habitus by Maria Laura Ruiu, Gabriele Ruiu, and Massimo Ragnedda



Abstract
This paper conceptualizes the techno-environmental habitus to explore differentiation among media users and their climate change awareness by adopting a dynamic concept that takes into consideration both pre-existing conditions and interactions with the technological field of action. The paper investigates the characteristics of multi-layered dispositions towards climate change in the U.K. through an online survey of a representative sample of the U.K. population (N=1,013). Results show that, despite the predominance of advocacy positions, four different techno-environmental habitus point to a fragmented landscape, but also a “chameleon”, transformative capacity of habitus, given that some common traits are shared by the groups. Beyond the four different patterns related to techno-environmental attitudes, one of the most interesting findings relates to the fatalistic techno-environmental habitus, which presents some traits in common with the scepticism and advocacy approaches but tends to be discouraged with regard to taking action. The identification of the nuances of techno-environmental habitus is relevant for climate change policy implementation because they may facilitate or hinder both individual and collective action.

Contents

Introduction
Conceptualizing the techno-environmental habitus
Methods
Results
Discussion
Conclusion

 


 

Introduction

This paper adopts the concept of habitus to interpret differentiation among technology users and their perception of climate change. The public disposition towards climate change is a relevant aspect of climate policy and is largely influenced by the use of news media (Schäfer and Painter, 2020). The originality of this work lies in exploring the interaction between techno-use and environmental dispositions, revealing different techno-environmental habitus, which may either facilitate or hinder both individual and collective sustainable actions.

Several studies in the U.K. have highlighted the persistence of scepticism around climate change and its multiple dimensions (in terms of existence, causes, consequences and actions needed) (European Perceptions of Climate Change Project [EPCC], 2017; Fisher, et al., 2018; Lorenzoni and Pidgeon, 2006; Poortinga, et al., 2011; Taylor, 2012; Whitmarsh, 2011). However, an increasing degree of acceptance of climate change has been observed to take place over time (Spence, et al., 2011). At the same time, opinion polls and the literature on the public perception of climate change show different levels of advocacy in the U.K., characterized by peaks and troughs (Capstick and Pidgeon, 2014; U.K. Department for Business, Energy & Industrial Strategy, 2013; Reser, et al., 2012; Stokes, et al., 2016; Taylor, et al., 2014; van der Linden, 2015). Despite an overall increase in the acceptance of climate change (Spence, et al., 2011), the U.K. still represents an interesting context due to the persistence of some resistance to belief in climate change-related risks (Fisher, et al., 2018; Poortinga, et al., 2011; Taylor, 2012; Whitmarsh, 2011). Moreover, as highlighted by Ruiu (2018), the relationship between the types of medium used and climate change perceptions still needs to be investigated. Previous studies showed that traditional mass media (television and newspapers and printed media) are fundamental sources of information about climate change (Schäfer, 2015; Schäfer and Painter, 2020; Ruiz, et al., 2020). Moreover, an increasing number of studies have also shown that online debates about climate change have been flourishing thanks to social media and the increasing use of the Internet as a source for scientific information. The investigation of climate change discussions on social media has become a focus of studies on public understanding of climate change (Connor, et al., 2016; Holmberg and Hellsten, 2016, 2015; Pearce, et al., 2015; Porter and Hellsten, 2014; Spartz, et al., 2015; Vraga, et al., 2015; Veltri and Atanasova, 2015). Some studies highlighted that exposure to user-generated content does not necessarily produce significant effects on the perception of climate change (Porten-Cheé and Eilders, 2015; Schäfer, 2012). By contrast, several studies found a link between people’s levels of awareness and engagement and their use of social media, thanks to the latters’ interactive character and the opportunity they offer for non-experts to express their opinions (Anderson, 2017; Boulianne, et al., 2020; Cody, et al., 2015; Mavrodieva, et al., 2019; Uldam and Askanius, 2013; Williams, et al., 2015). Thus, there is still a need to investigate how technologies interact with people’s environmental dispositions. This article investigates the characteristics of multi-layered dispositions towards climate change in the U.K. through an online survey of a representative sample of the U.K. population (1,013 respondents), which explores respondents’ use of media to search for information on climate change (both online and traditional media) and their climate perceptions. This study begins with explorative factor analysis (EFA) that, not surprisingly, indicates the emergence of two main factors related to climate change: “advocacy” positions (around 44 percent of the variance); and characteristics that can be associated with climate change “scepticism” opinions (around 18 percent of the variance). However, EFA shows that from the third factor onwards, the percentage of variation explained by additional factors is less than five percent, suggesting that between these two main factors, groupings are highly fragmented. For this reason, this work aims to further investigate potential nuances that might characterize intermediate positions between these two extremes. This will help to identify specific patterns of dispositions through the lens of a “techno-environmental” habitus. To shed light on the rise of the techno-environmental habitus, the article is structured as follows: the first section reviews the literature around technological habitus and environmental habitus and formulates the research hypotheses. The second section describes the methods used to analyse the data. The third section reports the findings and the fourth discusses the results. The final section presents the conclusions to be drawn from the study.

 

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Conceptualizing the techno-environmental habitus

This paper conceptualizes habitus as a dynamic concept, which is simultaneously a process and a product resulting from individual histories (Bourdieu, 1993) and the social world (Bourdieu and Wacquant, 1992; Schmidt, 1997). From this perspective, habitus is interpreted as a “bridge” between structure and agency [1]. Habitus is a long-life process whereby various kinds of capital are acquired from the early stages of life onwards and adaptions are made in response to external fields (DiMaggio, 1979; Reay, 2004), but it is also layered across society (Sterne, 2003). Habitus might be defined as a lens through which to interpret social practice (Elam, 2008) that results from both individual and collective histories (Bourdieu and Chartier, 2015). Bourdieu (1990, 1977) interprets habitus as an unconscious force that, even though it cannot be deliberatively transformed, is able to adapt to new fields (Bourdieu, 2002). The notion of field is interpreted by Bourdieu and Wacquant [2], as a “space of social forces and struggles”. However, the struggles that characterize the field depend on social actors’ interests with regard to defining the meaning and rules of that specific context. In the case of climate change this corresponds to the attempt to define its multidimensional meanings (in social, as well as economic, terms). While the concept of field relates to agents’ positions in social space, habitus is concerned with how their position influences agents’ values and understandings as metabolized through social practice (Hughes and Paterson, 2017). The concept of habitus represents the link between individual actions and the field that is the context for these actions (Brulle and Norgaard, 2019). This interpretation suggests that individuals acquire a habitus, which in turn adapts to specific fields that are regulated by social norms. Therefore, the habitus might be interpreted as an individual’s competence to deal with social circumstances. However, as highlighted by Costa, et al. (2019), this concept has been questioned by the emphasis on the fluidity of risk/reflexive and morphogenetic societies (Archer, 2013). Nevertheless, the “dialectical confrontation” [3] between habitus and fluidity might be only apparent, since contextual factors (e.g., access and use of the media) might become an integral part of this unconscious force, given its simultaneously durable and flexible nature. Costa, et al. (2019) also identify two key institutions that contribute towards increasing such fluidity of society, which are higher education and the Internet. They observe a redefinition of an individual’s habitus in relation to a shift in the field that can lead to a shift in attitude and practice. The “out of environment” conception of experiences used here (Burke, 2015) builds on Bourdieu’s assertion that, while the habitus is quite durable, a large enough shift in the environment can lead to an altered habitus (Bourdieu and Wacquant, 1992). However, adapting to a new field also means that individuals are subject to two opposing forces, one that anchors them to their original field, and another that pushes them to develop a novel orientation. This raises several possible outcomes: the fragmentation of experiences might cause a rejection of the original habitus (Wentworth and Peterson, 2001) or a “chameleon” transformative capacity (Abrahams and Ingram, 2013), but may also result in uncertainty (Reay, 2005). Such fragmentation consequently requires exploration in the context of climate change to understand the stratifications of public dispositions that can hinder or facilitate policy-making.

The above-mentioned “chameleon” capacity of habitus has been studied separately in relation to technology use and environmental dispositions, respectively. On the one hand, the technological habitus has often been studied as an interaction between collective practice embodied in the habitus and individual action (Costa, 2014; Kvasny, 2005). It has been suggested that technology, interpreted as “social artefact”, cannot be separated from social practices, by contrast identifying a process of negotiation in relation to the field of use (Sterne, 2003). The concept of digital habitus has been described as a continuous and intense experience of digital technology (Richardson, 2015; Zevenbergen, 2007), which results from both the type of technology and users’ pre-existing ability to benefit from its use (Czerniewicz and Brown, 2013).

On the other hand, the concept of habitus has been applied to interpret environmental dispositions in terms of ecological or eco-habitus (Adams, 2012; Eriksen, 2013; Haluza-DeLay, 2008; Kasper, 2009; Kirby, 2017), which include social and ecological practices developed from a sense of place (Haluza-Delay, 2008; Smith, 2001) that influence tastes, practices and dispositions. It has been applied to the investigation of environmental social movements (Haluza-DeLay, 2008; Kasper, 2009; Kirby, 2017; Adams, 2012) and environmental communities (Kirby, 2018). However, an emphasis has also been placed on tastes or dispositions to protect the environment (Maguire, 2016) and existing high levels of cultural capital (Kirby, 2017). Research in the environmental field further supports that environmental dispositions should be interpreted as both a product of existing backgrounds and a process of relational practices (Hochschild, 2016; Kennedy and Givens, 2019). However, even though the concept of habitus has been applied to both technology-mediated practices and environmental dispositions, none of these studies considers the tripartite relation between existing backgrounds, technology use and environmental dispositions. Therefore, the present research aims to explore two main research questions related to i) the possibility of identifying layered dispositions towards the environment that interact with the use of technologies (techno-environmental habitus) to search for information on climate change (both online and traditional media); and, ii) the interaction between environmental dispositions and certain existing backgrounds (the unconscious drives of the existing habitus).

Since an increasing level of climate change acceptance has been observed over time in the U.K. (Spence, et al., 2011), but the persistence of scepticism (Author, 2020) and different levels of awareness have been identified (Capstick and Pidgeon, 2014; U.K. Department for Business, Energy & Industrial Strategy, 2013; Reser, et al., 2012; Stokes, et al., 2016; Taylor, et al., 2014; van der Linden, 2015), the first hypothesis assumes that various subgroups are positioned between acceptance and scepticism in relation to their techno-environmental habitus. This hypothesis is also supported by the EFA (see the Methods section), as presented in Table 3 and Figure 1, which demonstrate a “grey area” between the two polarized positions.

H1: Beyond the division between “scepticism” and “advocacy” positions, intermediate positions can be identified that correspond to different techno-environmental habitus.

We have referred to the concept of habitus as the individual dispositions, values and understandings of the social space/field, as internalized through social practice (Bourdieu, 1990). However, such an understanding is the product of the combination of existing backgrounds and social relationships that happen in a specific field (Hochschild, 2016; Kennedy and Givens, 2019). Therefore, in addition to the direct experience of a specific field, existing backgrounds are key elements for understanding habitus. Studies on environmental awareness are focused either on existing socio-demographic characteristics and psychological factors, or the behaviours of Internet users in specific contexts (e.g., social media). Among the sedimented existing aspects that characterize agents’ habitus, socio-demographic traits (Djoudi and Brockhaus, 2011; Zahran, et al., 2006) have been usually identified as predictors of climate awareness. Moreover, studies on climate change perception in the U.K. (European Social Survey, 2016; Fisher, et al., 2018) show that age and education are strong predictors of climate change awareness. Therefore, H2 assumes that the effects of these two socio-demographic characteristics (age and education) will predict climate change awareness to a significant level, regardless of the use of specific media to search for information on climate change. This main hypothesis is further divided into two sub-hypotheses.

H2a: The effect of age will be maintained in both models (with and without media effect) in relation to specific subgroups that might emerge from the explorative analysis.

H2b: The effect of education will be maintained in both models (with and without media effect) in relation to specific subgroups that might emerge from the explorative analysis.

 

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Methods

Sample

The online survey is based on a sample of the U.K. adult population (1,013 respondents, of which 541 female and 472 male) selected via the Toluna QuickSurveys platform. Even though it is a quota sample based on the voluntary participation of respondents, the sample appropriately captures the demographic stratification of the U.K. population. Given the increasing use in the U.K. of online technologies for accessing information about climate change (Lineman, et al., 2015) and the increasing number of Internet users (OFNS, 2019), an online survey can be appropriate, especially when investigating techno-behaviour and climate awareness. Tables 1 and 2 show the characteristics of the sample by age and educational background. These variables were shown to account for most of the variance in climate awareness according to relevant studies on climate change perception in the U.K. (European Social Survey, 2016; Fisher, et al., 2018).

 

Table 1: Age of respondents.
 Age 
18–3435–5455+Total
Total2713673751,013

 

 

Table 2: Educational qualifications.
 FrequencyPercentageCumulative percentage
ValidSome high school, no diploma908.98.9
 High school graduate26926.635.4
Some college credit, no degree21921.657.1
Bachelor’s degree32732.389.3
Master’s degree848.397.6
Doctorate242.4100
Total1,013100 

 

Analysis strategy

This work started with explorative factor analysis (EFA) that showed the emergence of two main factors related to advocacy (around 44 percent of the variance) and scepticism (around 18% of the variance) (see Table 3). These two factors, labelled as “scepticism” and “advocacy”, represented the starting point for the present work. Table 3 reports the loadings of the two factors and the related 16 items included in the factor analysis. Two factors were extracted according to an eigenvalue higher than one and a variance higher than five percent. Moreover, Table 3, shows the basis of our first hypothesis. It is clear from Figure 1 that a third “grey area” might be represented by undecided positions. The concept of techno-environmental habitus enables us to concretely explore how the use of media technologies are configured in specific settings to support environmental awareness.

To explore Hypothesis 1 (H1) and determine if more than two groups were generated by the combination of the two factors, hierarchical cluster analysis was conducted by adopting Ward’s cluster method (Ward, 1963) and the Squared Euclidean distance measure, followed by a K-means cluster analysis to optimize the results. The number of clusters (four) was determined through the elbow method by subtracting the step of ‘elbow’ from the number of cases. Once the number of clusters was determined, a K-means cluster analysis was performed. Table 5 reports the composition of the internal clusters by education, age group, and gender. Finally, to determine the significant traits of each group, a one-way ANOVA was performed between each item and the clusters. To evaluate the nature of the differences between the group means, the analysis was followed up with Tukey’s HSD post hoc tests.

To study the relationship between the new clusters and the frequency of use of both traditional and online media to search for information on climate change, two indexes were developed. An index of traditional media uses was created by combining three items related to the frequency of use of newspapers, television, and radio into a composite variable (Cronbach’s α = 0.717, M = 3.03, SD = 1.06). Respondents were asked to rate the frequency with which they use these media to get information about climate change on a five-point scale (ranging from 1 = never to 5 = frequently).

Similarly, an index of online media uses combined three items (Google searches, social media and online newspapers) in a composite variable (Cronbach’s α = 0.782, M = 2.82, SD = 1.20).

Hypothesis 2 (H2) and its related sub-hypotheses were investigated through a multinomial regression per bloc by exploring the relationship between the new clusters and media use. The first bloc analyses the relationship between demographic traits, such as age (M = 47.29, SD = 16.5), gender (n = 541 females, n = 472 males) and educational qualifications (Mdn = some college credit, no degree), and the four groups.

 

Table 3: Factor loading (scepticism and advocacy).
Note: Kaiser-Mayer-Olkin (KMO) test= 0.942; Bartlett’s test, p<0.000
 ScepticismAdvocacy
We can all do our bit to reduce the effects of climate change (action)-0.7150.322
People should be made to reduce their energy consumption if it reduces climate change (action)-0.5890.469
Climate change will improve our weather (consequences)0.4240.539
Climate change is just a natural fluctuation in Earth’s temperatures (causes)0.7560.360
It is already too late to do anything about climate change (action)0.5490.452
Human activities have no significant impact on global temperatures (causes)0.6930.432
Climate change is something that frightens me (existence)-0.5800.513
I am uncertain about whether climate change is really happening (existence)0.7390.424
Radical changes to society are needed to tackle climate change (action)-0.6790.409
The evidence for climate change is unreliable (existence)0.7500.374
Claims that human activities are changing the climate are exaggerated (causes)0.7430.395
If I come across information about climate change, I will tend to look at it (existence)-0.4990.497
The effects of climate change are likely to be catastrophic (consequences)-0.6890.430
Nothing I do makes any difference to climate change one way or another (action)0.7140.332
Experts are agreed that climate change is a real problem (existence)-0.6590.356
I feel a moral duty to do something about climate change (action)-0.7040.445

 

 

Distribution of scepticism and advocacy factors
 
Figure 1: Distribution of scepticism and advocacy factors.
Note: The Advocacy and Scepticism variables, generated through the EFA, were converted to a range from 0 to 100 to simplify the interpretation.

 

 

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Results

Four clusters were found through the analysis to be optimal for grouping the cases. Figure 2 shows how the four groups are distributed and grouped in relation to their degree of awareness, from complete scepticism to advocacy. To identify the characteristics of the four groups and the differences between them, which can be translated into different techno-environmental habitus, a one-way between-groups ANOVA was performed between each item included in the factorial analysis (independent variables) and the four clusters (dependent variables). The between-groups ANOVA yielded a statistically significant effect per each model. Table 4 summarizes the results of Tukey’s HSD post hoc tests that show differences and similarities between the four clusters.

The first group can be labelled as an “advocate” group and it is characterized by an intention to act, such as being disposed towards reducing energy consumption, advocating radical changes and conceptualizing action as a moral duty. This group also recognizes the scientific consensus around climate change and tends to search for information about it. Finally, it also predicts the frightening, catastrophic consequences of climate change. Group two can be labelled as a “fatalist” group and it is characterized by agreement with items that see any intervention as useless because “it is too late” and “nothing can make a difference”. Moreover, no responsibility for climate change is attributed to human causes. However, this group shares some common traits with both the scepticism and advocacy groups. In the first case, it interprets evidence of climate change as unreliable, climate change as being uncertain, natural and potentially beneficial to the weather, and the impact as being exaggerated. At the same time, in line with the advocacy group, this group searches for information about the phenomenon, climate change frightens them, and they support a reduction of energy consumption. The third group can be positioned in the middle as “indecision” because they are not characterized by the prevalence of specific characteristics in comparison to the other three groups. Finally, the fourth group (scepticism) is characterized by the interpretation of climate change as a natural phenomenon, the scientific evidence as unreliable, the claims of impacts as being exaggerated and the belief that personal actions are useless.

 

Table 4: Differences and similarities between the four clusters (one-way ANOVA).
Note: *. The mean difference is significant at the p = 0.05 level.
a. The group sizes are unequal. The harmonic mean of the group sizes is used. Harmonic mean sample size = 173.919.
 AdvocacyFatalismIndecisionScepticism
We can all do our bit to reduce the effects of climate change4.79*4.33*3.91*2.769*
Radical changes are needed to tackle climate change4.53*4.24*3.62*2.25*
The effects of climate change are likely to be catastrophic4.41*4.10*3.35*2.19*
Experts are agreed that climate change is a real problem4.51*4.13*3.64*2.34*
I feel a moral duty to do something about climate change4.42*4.16*3.43*1.98*
People should be made to reduce their energy consumption if it reduces climate change4.274.273.53*2.55*
Climate change is something that frightens me4.074.143.05*1.60*
If I come across information about climate change, I will tend to look at it4.074.203.29*2.37*
It is already too late to do anything about climate change1.95*3.88*2.61*3.24*
I am uncertain whether climate change is really happening1.53*4.10*2.74*3.64*
Climate change is just a natural fluctuation in Earth’s temperatures1.90*4.133.05*4.20
The evidence for climate change is unreliable1.74*4.123.00*3.90
Claims that human activities are changing the climate are exaggerated1.63*4.152.85*3.92
Nothing I do makes any difference to climate change one way or another1.78*3.902.77*3.77
Climate change will improve our weather2.17*4.15*2.792.91
Human activities have no significant impact on global temperatures 1.39*3.41*2.50*4.02*

 

 

Distribution of the four techno-environmental habitus
 
Figure 2: Distribution of the four techno-environmental habitus.

 

 

Table 5: Socio-demographic traits of the clusters.
EducationAgeGenderScepticismIndecisionAdvocacyFatalism
Some high school, no diploma35–54F2622
M2452
55+F1955
M71486
18–34F0211
M1221
High school graduate35–54F718195
M615227
55+F724293
M912231
18–34F1141815
M1751
Some college credit, no degree35–54F615186
M314153
55+F412141
M422233
18–34F015184
M2872
Bachelor’s degree35–54F6262513
M715263
55+F312252
M523341
18–34F1212715
M0121114
Master’s degree35–54F1826
M3283
55+F0131
M0460
18–34F17128
M0224
Doctorate degree35–54F0010
M0026
55+F0030
M1320
18–34F0110
M0103
Total  91351424147

 

Given the categorical nature of the cluster membership, in order to analyse the relationship between cluster allocation, demographic traits, and media behaviour, two multinomial regressions were performed (Kwak and Clayton-Matthews, 2002; see Table 6). The category of “advocacy” was adopted as a reference since this is the most frequently occurring (42 percent). Model 1 only includes socio-demographic variables and explains 11 percent of the variance, whereas Model 2 also includes media use and explains 20 percent of the variance.

In both cases, sex does not contribute significantly to the models. Fatalists tend to be younger than advocates. This is also confirmed by the second model, which includes the media variables. Moreover, both models show significant differences between those with some higher or secondary education and those with a doctorate. Doctorate holders are more likely to be fatalists than advocates. By contrast, the second model shows that when the media effect is considered, education is no longer a significant predictor of fatalism. Finally, being a fatalist is more likely to be connected with higher use of new media compared with advocates.

Moreover, age becomes a predictor of being undecided only when the media effect is considered. Advocates tend to be older than undecided individuals. However, the use of both new and traditional media is associated with higher probabilities of being an advocate rather than undecided.

Similarly, in the case of sceptics, the second model shows a significant effect of age on being sceptical. In this case, older age is also associated with higher scepticism. However, sceptics are less likely to use both traditional and new media. Finally, the model supports that a higher degree of scepticism is associated with a lower level of formal education.

Therefore, advocates tend to use both kinds of media (traditional and new) more than sceptics and the undecided. However, the use of new media is also associated with higher degrees of fatalism. H2 (a and b) is only partially supported. It turns out that the effect of both age and education is maintained in both models (with and without media effect) in relation to a specific subgroup, the one related to fatalism. However, in the case of both the undecided and the sceptics, some socio-demographic traits (age in both cases and education in the case of sceptics) become significant predictors only when the use of media is considered.

 

Table 6: Multinomial regression per bloc.
Note: *p<0.01 **p<0.05
 Model 1Model 2
Model chi-square=108.557 (p<0.000); Goodness of fit: Person chi-square=1301.555 (p=0.884); Deviance chi-square=1229.620 (p=0.286); Nagelkerke= 0.111Model chi-square=205.274 (p<0.000; Goodness of fit: Person chi-square=3042.349 (p=0.047); Deviance chi-square=2220.950 (p=1); Nagelkerke= 0.203
BStd. errorExp(B)BStd. errorExp(B)
The reference category is advocates
FatalismIntercept2.095*0.585 0.8350.761 
Exact age-0.048*0.0070.954-0.046**0.0080.955
Some high school/no diploma.1630.5991.1770.3760.6371.456
Some college credit-1.368**0.5400.255-1.331*0.5770.264
High school graduate-1.741*0.5610.175-1.646**0.5960.193
Bachelor’s degree-1.285**0.5270.277-1.3030.5640.272
Master’s degree-0.7630.5750.466-0.8570.6120.424
Ph.D.Ref.     
Female0.1000.2091.1050.1550.2151.168
MaleRef.     
Traditional media/technology   0.0820.1241.085
New media/technology   0.264**0.1331.302
IndecisionIntercept-0.2510.608 1.382*0.690 
Exact age-0.0070.0050.993-0.012*0.0050.989
Some high school/no diploma1.1280.6213.0890.7960.6452.216
Some college credit0.3110.5781.3650.1210.6021.129
High school graduate0.4620.5791.5880.2620.6041.300
Bachelor’s degree0.2470.5741.2800.1820.5981.200
Master’s degree0.1950.6221.2160.1270.6471.135
Ph.D.Ref.     
Female0.0600.1491.0620.0800.1531.083
MaleRef.     
Traditional media/technology   -0.265**0.0840.767
New media/technology   -0.186*0.0890.830
ScepticismIntercept-2.6621.134 0.1431.2351.002
Exact age0.0100.0081.0100.002*0.0080.565
Some high school/no diploma1.5531.1144.7241.238**1.1513.447
Some college credit0.9651.0772.6250.8191.1162.268
High school graduate0.6591.0861.9330.6021.1251.825
Bachelor’s degree0.3781.0811.4590.5001.1211.649
Master’s degree0.4601.1621.5840.5291.2041.697
Ph.D.0b  0  
Female-0.2770.2390.758-0.2310.246 
MaleRef.     
Traditional media/technology   -0.571**0.1450.793
New media/technology   -0.331*0.1420.718

 

 

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Discussion

The first hypothesis related to the existence of layered groups that are associated with different techno-environmental habitus is supported by the analysis, which identifies four different patterns that combine attitudes to the environment and the use of technology. However, one of the most interesting aspects resulting from clustering the groups in relation to their degree of scepticism/advocacy is the emergence of a fourth group related to fatalism. This group shares some aspects with both scepticism and advocacy groups. In the first case, they tend to believe that it is not worth taking action in relation to climate change because it is too late (see also Feinberg and Willer, 2011; Thompson, 2003) and its consequences are inevitable (Kollmuss and Agyeman, 2002; Lorenzoni, et al., 2007; Simonet and Fatorić, 2016), but also that it is exaggerated (McNeish, 2017), as is the human contribution to the phenomenon. However, in the second case, the fatalistic habitus is also found to be anxious about the potential consequences of climate change. Given that in the U.K., fatalism has been found to inhibit individual changes and perceptions of climate change (Lorenzoni, et al., 2007), this result is interesting for policy-makers aiming to increase people’s active engagement. In fact, previous studies have shown that when climate change is perceived as “out of human control” people’s behavioural responses are affected, as is their perception of risk (Mayer and Smith, 2019). As highlighted by Suthirat and Takashi (2013), fatalists are usually neglected by policy-makers due to their status as “non-actors”. Conversely, in order to engage fatalists to take action about climate change it is important to make them understand the importance of collective social responsibility. In light of this aim, it is relevant to consider a number of socio-demographic traits, which have been taken into consideration by the second hypothesis and its related sub-hypotheses. Certain of these characteristics become significant when the media effect is taken into account. When the layered nature of the techno-environmental habitus is considered, the effect of sex on climate change awareness disappears. However, some other traits such as age become important predictors. Advocates are found to be older than both fatalists and the undecided, but younger than sceptics. The influence of both age and education (with and without media effect) is maintained in relation to fatalism. However, in the case of both the undecided and sceptics, certain socio-demographic traits (age in both cases and education in the case of sceptics) become significant predictors only when the use of the media is considered.

The literature strongly connects habitus to cultural capital, which is often found to be culturally mediated by educational qualifications. Surprisingly, both models show that fatalists tend to be highly educated (more likely to be qualified to Ph.D. level than advocates). This aspect needs to be further investigated to understand the relationship between fatalism and beliefs about climate change. However, one speculative explanation might be that those who are highly educated might interpret communication around climate change as “exaggerated”. In turn, this might increase uncertainty and perception of climate change as out of human control. One might expect this interpretation to be connected to the higher use of traditional media and older age. However, also surprising is that fatalism is associated with higher use of new media and younger ages compared to advocates. By contrast, in line with the literature, higher scepticism about the reality, causes and consequences of climate change tends to be associated with a lower educational level than advocates, but only when the model also includes media effects. These results suggest the importance of simultaneously considering the tripartite relationship between habitus, technology use, and environmental dispositions. In this sense, the use of a habitus lens of analysis overcomes the binary division between structure and agency and allows action to be contextualized and brings into consideration potential factors that can influence, promote or constrain environmental awareness, such as the use of media.

The use of new and traditional media is associated with higher levels of advocacy and decreasing levels of both scepticism and indecision. This is an important insight for policy-making aimed at tackling climate change and promoting a sustainable future. However, these results also show that the use of media alone cannot guarantee the promotion of advocacy. In fact, higher uses of new media might produce contradictory results in terms of increasing fatalist approaches to the problem. This may be dependent on the types of information accessed.

 

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Conclusion

This empirical investigation suggested that the application of the concept of techno-environmental habitus might help identify the variety of dispositions towards climate change, also taking into consideration the use of technologies to search for information around climate change. The identification of a layered techno-environmental habitus might in turn help in understanding what actions should be implemented to promote awareness and tackle resistance to accepting the reality of climate change, thus contributing to a (more) sustainable society.

Despite the predominance of advocacy positions, the identification of four different techno-environmental habitus presents a fragmented landscape, but also indicates a “chameleon”, transformative capacity of habitus, given that some common traits are shared by the groups. This represents a starting point for policy-making oriented towards increase the acceptance of climate change, which can lead to a shift in attitudes and practices. However, the explorative character of this research only provides a general overview of the potential relationships between existing socio-demographic characteristics and individuals’ technological/environmental predispositions. Further research might look into the interaction between existing backgrounds and the adaptive capacity of the techno-environmental habitus from a qualitative perspective. We have conceptualized the techno-environmental habitus to explore differentiation among media users and their climate change awareness by adopting a dynamic concept that takes into consideration pre-existing conditions and the interaction with the technological field of action. Beyond the four different patterns related to techno-environmental attitudes, one of the most interesting aspects relates to the fatalistic techno-environmental habitus, which presents some traits common to scepticism and advocacy, but tends to experience discouragement with regard to taking action. This also represents an interesting category that requires further investigation from a qualitative point of view. It emerges that the “bridging” nature of habitus is evident in this group, given the interaction between existing pre-conditions (socio-demographic traits) that become significant when the media effect is considered. This study showed that this group tends to be highly educated and its fatalistic disposition towards climate change is associated with higher use of new media technologies and younger ages. The use of digital technologies, thus, has an important role to play in promoting a sustainable approach to life (Ragnedda, 2020). It can be anticipated that further studies into postgraduate education students (who are acquiring cultural capital) and their use of technologies to inform their environmental awareness might help in understanding the higher predisposition of some highly-educated individuals, who are also users of new media, to adopt a fatalistic outlook. In this direction, a longitudinal study that follows students starting from undergraduate education (and potentially, those beginning postgraduate programmes) might be useful in developing an understanding of the evolution of the techno-environmental habitus, throughout the course of higher educational formation. Future studies could also go further in exploring the reasons for the relationship between cultural capital and techno-environmental habitus. Despite the descriptive nature of this study, this paper has identified a number of interactions between existing backgrounds, technological uses and environmental dispositions, demonstrating that the concept of techno-environmental habitus is a valuable tool for studying the variety of dispositions towards climate change. In turn, understanding the characteristics of such a stratified techno-environmental habitus can help formulate concerted policies that simultaneously take into account technology use and the environment. End of article

 

About the authors

Maria Laura Ruiu is Senior Lecturer in the Department of Social Science at Northumbria University in Newcastle, U.K.
E-mail: maria [dot] ruiu [at] northumbria [dot] ac [dot] uk

Gabriele Ruiu is a research fellow in the Department of Economic and Business Sciences DI at the University of Sassari in Italy.
E-mail: gruiu [at] uniss [dot] it

Massimo Ragnedda is Senior Lecturer at Northumbria University in Newcastle, U.K.
E-mail: massimo [dot] ragnedda [at] northumbria [dot] ac [dot] uk

 

Notes

1. Crossley, 2002, p. 177.

2. Bourdieu and Wacquant, 1992, p. 102.

3. Bourdieu, 2002, p. 31.

 

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Editorial history

Received 10 September 2021; accepted 8 October 2021.


Copyright © 2021, Maria Laura Ruiu, Gabriele Ruiu, and Massimo Ragnedda. All Rights Reserved.

Conceptualizing the techno-environmental habitus
by Maria Laura Ruiu, Gabriele Ruiu, and Massimo Ragnedda.
First Monday, Volume 26, Number 11 - 1 November 2021
https://firstmonday.org/ojs/index.php/fm/article/download/12353/10515
doi: https://dx.doi.org/10.5210/fm.v26i11.12353