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In Chapter 3, the importance of identity processes to group behaviour was introduced and in the main the evidence from the three studies presented in the present chapter has supported this work. In Chapter 5, literature was presented which argued that diversity had the potential to fragment social groups and it was suggested that one way to deal with this was through the development of a pro-diversity culture (Tyler & Blader (2000); van Knippenberg & Haslam (2003); van Knippenberg, Haslam & Platow (2004). Taken together the studies presented in this chapter provided evidence for a “value in diversity” model for solving the problem of crew heterogeneity in general and perhaps in the space flight context. Study 2 provided further evidence that identification processes and associated outcomes could be reliably assessed and that the pattern of relationships between variables was as would be expected based on previous social psychology theory and research. In particular, group identification and measures of individual and sub-group alienation were significantly and strongly related. These alienation measures are taken as an indicator of a group’s success with dealing with conflict and diversity and also an indicator of negative group outcomes. Study 3 also showed that in the context of diversity amongst group members, a group norms where such diversity is valued and group defining had an impact on group outcomes. Again alienation was less likely where diversity was made explicit in the group but there was a pro-diversity compared to a pro-uniformity group norms.

Study 4 provided stronger evidence of these same patterns but using broader measures of group functioning that included alienation as well as decision-making and

organisational citizenship or pro-social behaviour. Building on the outcomes and limitations of earlier work in this thesis, Study 4 in this chapter provided the strongest evidence yet to support the core hypotheses of the thesis. Not only were there strong relationships between group norm (pro-diversity or pro-uniformity) and group functioning measures there was evidence that such relationships were related to the level of psychological connection between the individual and the group. In this way, as predicated social identity processes were demonstrated to play an important role. Ideally, given the aim of the thesis to demonstrate these group processes at work in the spaceflight context, these same variables would be shown to be important and related in a more naturalistic setting. The next chapter outlines such a study which was conducted during a winter-over period at an Antarctic research station.

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- Chapter 7 -

Diversity Culture in Antarctica: A Winter Over Study at

the Concordia Research Station

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7.1 Introduction

In the last chapter three studies were described that investigated how the content of a social identity, in this case an identity which valued the diversity of group members, impacted on ingroup identification, levels of alienation and various other aspects of group functionality. The third study described in the last chapter found strong statistical evidence for the predicted effects; however because this study was a vignette it had very low ecological validity. The first study described was the only one of the three studies which did have high ecological validity, but the small sample size and data set, meant that statistical inferences making was somewhat problematic. The conclusion of the last chapter was that in order to find significant evidence for the importance of identity processes in extreme environment situations and the potential benefits of diversity cultures, a study which had high ecological validity and a large data set was required. The current chapter outlines such a study, which was conducted during the Antarctic winter of 2006, at the Concordia research station.

Antarctic research stations during the winter over period provide one of the most ideal places on Earth to conduct psychological space analogue research (Suedfeld & Weiss, 2000). People at these stations experience long-term geographic isolation; they live in confined habitats, have small group sizes, are exposed to real physical dangers, are psychological screened prior to embarkation, and undertake scientific and technical activities similar to those conducted during space flights. For all purposes they represent a true isolated confined extreme environment. In almost every way, space psychology studies conducted in these environments have higher ecological validity than anywhere else on Earth.

Due to the scarcity of research stations that are crewed during the winter-over period, it is also extremely difficult to get access to conduct psychological research. Generally research proposals need to be submitted a number of years in advance and are thoroughly screened and assessed on their merits. In order to conduct the study presented in this chapter, a proposal was submitted for review to a committee within the European Space Agency (ESA). The Concordia research station was built by the French Polar Institute and Italian Antarctic Programme for the purpose of conducting space related research; however research there is managed by the ESA. The process to be included in the 2006 research program was competitive with only a small number of studies selected. The study presented in this chapter therefore represents a very rare opportunity to conduct psychological research in such an excellent space analogue context.

In order to take full advantage of this opportunity, the fifth study of the thesis was devised in such a way as to utilise some of the newest and most advanced statistical tests available. By doing this it was hoped that the data could be interpreted in an effective and statistically robust way. As in the first and second study, this data set would be non- independent, meaning that standard statistical testing could not be conducted. Unlike the second study however the eight month winter-over period provided an opportunity to collect data on many occasions. So like in the first study of the thesis, Multilevel Linear Modelling could be used to model relationships between variables. In addition to this however, another technique was utilised which takes full advantage of the interdependencies within the data set. This technique is Social Network Analysis and involves the quantification and modelling of network data. In other words it models the relationships between different individuals and can be used to understand the social structures that exist within groups.

Social Network Analysis is not new to extreme environment research and an example can be seen in the research by Johnson, Boster, and Palinkas (2003). The present study however will be the first time that such a technique has been used to explicitly document identity processes in an extreme environment. It will also be the first time that any major social psychological theory has been attempted to be modelled using social network techniques in an ICE environment (see also Copeland, Reynolds & Burton, 2008 for the use of such techniques in an organisational sample).

Network data is different from traditional data sets as it is comprised of “ties” between agents within a network. A social network it is made up of relational data and

describes the nature of the connections between individuals in the domain of interest. These connections can describe a range of constructs often including communication, trust, friendship and cooperation. In its basic form network data allows for these connections to be graphed so that the relationships can be viewed and interpreted visually. This use of social network techniques allows for the observation of social structures, without detailed quantification. More advanced methods of interpreting social networks have also been developed however. Hanneman and Riddle (2005) for example describe a range of ways that social relations can be modelled using Social Network Analysis. They use network structures such as “global coherence” to develop advanced statistical models. A globally coherent network for instance can be described as “one that forms a single group composed of a unitary core and periphery and lacks clearly defined cliques or subgroups” (Johnson, Boster, & Palinkas, 2003, pg 98). Using Social Network Analysis, it is possible to build statistical models in which a variable (such as diversity culture), can be used to predict social structures like global coherence. In this way it provides an opportunity to measure and analyse group dynamics on an interpersonal and group level. For isolated groups of continuously interacting individuals, such as is found in Antarctica, this methodology can effectively be used to answer social psychological questions.

In the context of the current research, both ingroup identification and the extent to which a group has a pro-diversity culture can be used to predict social network structures over time. Research from social identity theory and self categorisation theory suggests that groups within which members identify highly with their group tend to be more functional (in term of factors such as cooperation, trust, communication), if this is the case it would be expected that these groups would have a higher number of ties between individuals in these domains. So for example a network showing cooperation ties between individuals, would have more connections if those individuals all identified with their common ingroup. In this study as we are only studying one particular group, these effects can be expected to be observed over time.

From the literature reviewed in Chapter 5 and the findings from Chapter 6 we would also expect similar findings in relation to diversity culture. For example when the expedition group endorsed a pro-diversity norm we would expected it to have less fragmentation (isolated individuals or subgroups) within networks that describe pro-social relationships. In this way a social network analysis enables us to measure the impact of

these social psychological variables on the relationships between individuals and to observe the effects on relational structures.

In addition to non-relation variables (variables which do not indicate ties between individuals) predicting network structures, one kind of network can be used to predict another. In the case of the current research, a network which shows which people think they are similar to one another could be used to predict which people socialise with one another. This kind of analysis would be particularly informative as it could demonstrate directly how perceptions of diversity impact upon group structures. In this way Social Networks Analysis can be used to model how different networks relate to one another within a given data set.