Measuring Social Sustainability

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Measuring Social Sustainability:A Community-Centred Approach

Liam Magee & Andy Scerri & Paul James

Received: 28 August 2011 /Accepted: 19 January 2012

# Springer Science+Business Media B.V./ The International Society for Quality-of-Life Studies (ISQOLS) 2012

Abstract Efforts to measure social and community sustainability confront a series of methodological dilemmas. We present four key distinctions that tendto orient such efforts: between objective and subjective assessment; between communities as the sum-of-their-parts, or as holistic and distinct entities inthemselves; between present and future aspects to be measured; and betweenuse of top down and bottom up indicators. We then propose a question-naire for sustainability assessment in light of these. We administered thequestionnaire to various communities in the Middle East, South and South East Asia between 2006 and 2010, and present descriptive summaries and a factor analysis of the results here. The results serve two aims: to augment existingqualitative research conducted in the respective areas, and to test the validityand reliability of the instrument itself. Several limitations of the questionnaireemerged during analysis, which we discuss. The results also show strongcorrelation with national Human Development Index figures for the communi-ties surveyed and moreover, point to several interesting attitudinal divergences

between the communities sampled. We conclude with an outline of a revisedsustainability assessment instrument that has application for research looking to bridge the gap between psychological orientations towards wellbeing, on theone hand, and sociological or organizational studies on sustainability, on the other hand.

Keywords Community . Wellbeing . Quality of life . Sustainability . Indicators

Applied Research Quality LifeDOI 10.1007/s11482-012-9166-x

L. Magee : A. Scerri : P. JamesSchool of Global Studies, Social Science and Planning, RMIT University, Melbourne, Australia

L. Magee ( * )RMIT University, 96.2.7c, 17 Lygon Street, Carlton VIC 3053, Australia e-mail: [email protected]


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Introduction

Understanding the uneven resilience of communities has been a preoccupation of thesocial sciences since the nineteenth century. Classical social theory and sociology was

preoccupied with themes and questions about the cohesion, stability and integrationof communities. While terminology has changed, debates in this area are still to beresolved. Despite, or perhaps because of this lack of resolution, enquiry over the past two decades has shifted sideways to potentially more fruitful lines of inquiry. Thetask of understanding society , and more locally, community , has increasinglyintersected with a new set of preoccupations sustainability, wellbeing and quality of life. The underlying task of enquiry thus has moved, at least rhetorically, fromquestions of social structure, regulation and function, to more agency-focussedquestions dealing with issues such as sense of sustainability, community, wellbeing,

quality of life, security from

risk

or inclusion and participation.We identify four common dilemmas in the measurement of community sustain-

ability. The first of these relates to what is measured by indicators whether theymeasure objective conditions of a community, or to those conditions as subjectivelyexperienced by its members (Diener 2006 ; McCrea et al. 2006 ). A second andassociated dilemma concerns the ontological status of community itself. Is communityas an entity reducible to the sum of its parts, or rather is it constituted as an integratedobject beyond its parts (Sirgy 2010 ). A third dilemma concerns the temporal orien-tation of assessment. We suggest that an important distinction between wellbeing and

quality of life, on the one hand, and sustainability studies, on the other, fundamentallyconcerns this temporal dimension while notions of quality of life and wellbeingtend to assess past and present states of communities and individuals, sustainabilitycan be broadly conceived as oriented towards future states. The fourth dilemma,epitomized in the distinction between so-called global, or top down , and local, or bottom up assessment approaches, concerns whether to apply universal indicatorssets which lead to comparability but tend to ignore local, community-based mean-ings of sustainability or whether to devise context-specific indicators, selected byand relevant to the communities themselves, but requiring interpretation and transla-tion in order to compare communities meaningfully (Agger 2010 ; Fraser et al. 2006 ).

It is in this context that we developed a questionnaire instrument that provides anintegrated assessment of community sustainability. The particular instrument weintroduce is oriented towards these dilemmas in the following ways. It aims tomeasure the subjective attitudes of a community towards sustainability. It is gearedtowards understanding these attitudes both individually and as they relate towards thecommunity as a whole, thereby treating community as a distinct and irreducibleentity. It focuses upon both present wellbeing and future sustainability of the com-munity. Finally, it adopts a top down approach, where variables are predefined.Hence, in this conception of sustainability, the kinds of theoretical distinctionsintroduced above between global and local, objective and subjective, holistic andindividualistic, and present and future frames are both important to distinguish but invariably intertwined. Analytically, this suggests that contemporary communitiesneed to be understood as upon reflection they would understand themselves asenmeshed in global systems while striving for local autonomy; as entities that can beobjectively studied but also with validly subjective interpretations of their conditions;

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as coherent but necessarily fragmentary collections; and with a present sense of wellbeing heavily conditioned by concerns about sustainability.

Although our variables are predefined in the questionnaire, we acknowledge theneed in other work for complementary grounded or engaged theoretic approaches

(James et al. 2011a , b), to elicit community-based definitions and indexes of wellbeing. Similarly, while here we pursue a strategy of eliciting individual responsesthrough a sampling questionnaire, we also acknowledge that a rounded picture of community sustainability requires considerable further elaboration, for examplethrough more specific economic, ecological, political and cultural sustainabilityindexes. We endeavour to reflect some macro-level features by extending our set of variables to measure participant attitudes not only towards their own personal, or subjective, wellbeing, but also towards the broader, intersubjective wellbeing of their community. The strength of this assessment tool lies, though, in the other two vectors

of the dilemmas posed above. It does so, first, in assessing sustainability as experi-enced by the community itself; and, second, in combining existing wellbeing indi-cators with a series of supplementary variables aimed at eliciting responses to futurecommunity sustainability challenges. While the questionnaire does not measuresustainability definitively, by measuring a cross-section of community attitudes it can contribute towards better sustainability assessment, augmenting both qualitativestudies and objective indices such as the Human Development Index (HDI).

We applied the tool in a series of pilot studies with various Global North andGlobal South communities, each with distinct characteristics. Here the distinction

between North and South is treated as socio-economic distinction based on a geo-graphical tendency for poorer countries to be located in the southern hemisphere. Thestudies were part of an ongoing theoretical and empirical engagement with at-risk communities that also included qualitative ethnographic studies. In particular, assess-ing the sustainability of communities in Global South regions requires sensitivity tohow these features are constructed and measured. Not only are many of thesecommunities spatially, politically and economically isolated, they are increasinglyat risk from environmental, economic and cultural hazards brought about, at least in part, by ever-expanding global industrialization, and commensurate patterns of con-sumption and production. Growing awareness of these risks within communitiesthemselves means that objective conditions are increasingly reflected though not necessarily directly mirrored by subjective experiences. Moreover, the present assessment of quality of life in these communities is heavily tempered by anxietiesabout how sustainable their ways of life can continue to be. Increasingly communitiesare agitating for assessment tools that enable them to manage inevitable transitions brought about by processes of globalization and climate change, and preserve what they can of their traditions.

The research presented in this article thus had several distinct aims. Firstly, wewere interested in examining whether a generalizable questionnaire could accuratelymeasure subjective attitudes of members across diverse sites and communities, andsupplement information available from other sources. For this purpose we used twoforms of control: ethnographic research conducted at the communities, and generalHDI statistics for the countries in which the communities reside. Secondly, weinvestigated whether salient differences existed between communities in low andhigh-income countries towards different sustainability dimensions. In the context of

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the communities surveyed here, these differences further point to what may, givenfurther study, prove to be important distinctions between communities in the Northversus the South. Finally, the questionnaire is based upon an alternative theoreticalconception of sustainability to the common triple bottom line paradigm, as we

discuss further below. We therefore used the questionnaire as a form of extended pilot, during which this conception was further developed, and in turn led to a reformulation of the questionnaire itself, which we present below.

We begin in the next section by surveying briefly current trends in wellbeing andsustainability indicator development. We then introduce our own sustainability ques-tionnaire with an overview of its theoretical basis, and discuss pilot studies using thequestionnaire, conducted with a range of communities in the Middle East, South andSoutheast Asia. We include a range of communities in the Global South, and alsoinclude several communities from Israel and Australia, for comparative purposes.

These communities were surveyed between 2006 and 2010, in conjunction withqualitative studies. We then discuss our results, along with several limitations that emerged during these pilots. We conclude with an outline of a new version of thequestionnaire, that includes some possible remedies, along with final observations.

Measuring Sustainability, Wellbeing and Quality of Life

The literature on sustainability, wellbeing and quality-of-life indicators has flourished

over the past two decades. So has the number of projects attempting to quantify andqualify these concepts. In relation to wellbeing and quality-of-life, considerableeclecticism exists among proposed indicator systems, with variation introduced byscope (global, national or community-based), domain (life versus domain satisfaction(Diener 2006 )), demographic, geographic and cultural factors (Martin et al. 2010 ),orientation (objective versus subjective (McCrea et al. 2006 )), theoretical conceptionsof wellbeing (McMahan and Estes 2011 ) and statistical interpretations (Rojas 2011 ).A further key distinction evident in early debates in the literature contrasts liveabilitywith comparison theories of quality of life. While liveability theory held that persons

judgements about quality of life referred to absolute standards or universalizablenorms, comparison theory held that people make judgements about quality of life based upon comparison with some past experience, or with their own perceptions of the experiences of others (Veenhoven and Ehrhardt 1995 ). In recent years, researchershave attempted to combine the two theories by proposing the view that persons

judgements about quality of life implicate both absolute standards and recent changesin quality of life (Hagerty 1999 ).

Quality-of-life and sustainability literatures have historically been somewhat di-vergent, with efforts to measure sustainability showing a similarly rich and complextradition. The broadening out of conceptions of sustainability in the 1990s, most notably after the UNCED conference in 1992 (United Nations 1992a , b), led tovarious compositional definitions including, most famously, the triple-bottom-lineapproach encompassing environmental, economic and social dimensions (Elkington1997 ). Reflecting this diversity, in 2003, estimates of the number of sustainabilityindices alone already exceeded five-hundred sets (Parris and Kates 2003 ). As thoseauthors and others have suggested, the proliferation of indicator sets stems from the

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many divergent views and corresponding definitions of sustainability (Bohringer andJochem 2007 ; McCool and Stankey 2004 ; Munda 2005 ; Parris and Kates 2003 ).Among the operant distinctions are those between strong and weak definitions of sustainability (Atkinson 2000 ); between top down (expert-driven) and bottom up(community-driven) indicator development (Fraser et al. 2006 ); and between economic ,ecological and holistic or indexical approaches towards measurement (Bramley andPower 2009 ; Singh et al. 2009 ).

Similarly, a host of different methods have been employed for measuring sustain-able development, adopting a range of biophysical, econometric and human devel-opment models (Gasparatos et al. 2008 ; Parris and Kates 2003 ; Wilson et al. 2007 ).Finally, sustainability indicators have also integrated into a variety of broader frame-works oriented towards stakeholder engagement, policy and planning practices,including multi-criteria analysis (Balana et al. 2010 ; Munda 2005 ), integrated

assessment (Hettelingh et al. 2009 ; Krajnc and Glavic 2005 ; Lee 2006 ), transitionmanagement (Schilperoord et al. 2008 ), and various forms of strategic environment assessments (Pope et al. 2004 ).

Recently, there has been some convergence between these large bodies of litera-ture, as substantial research points to the often intimate connections between indi-viduals perceptions of their own absolute and relative quality of life, and thesustainability of the cultural, communitarian and organizational contexts in whichthey find themselves (Holden 2007 ; Kilbourne 2006 ; Assche et al. 2010 ; Kruger 2010 ; Matarrita-Cascante 2010 ).

Community settings often make ideal units of analysis through which to study theoverlay between individual wellbeing and social sustainability in particular, and haveincreasingly been studied in both respects (Agger 2010 ). Communities themselveshave been widely studied, both as psychological collectives, and as strongly cohesivesociological entities. We draw here upon canonical representations of both concep-tions in our understanding and subsequent measurement of community sustainability.In describing the psychological sense of community, McMillan and Chavis ( 1986 )identify four components: membership , influence , integrat ion and fulfilment of needs ,and shared emotional connection . In a similar vein, but abstracted into more gener-alized sociological terms, Putnam s reintroduction of social capital as a distinctiveand distinguishing feature of social networks, and particularly of bonding capital inrelation to homogenous social groups, offers a guiding if problematic notion for what it is that comprises communities, and what, consequently, needs sustaining for their continued survival.

Against this background of theoretical distinctions in the sustainability and wellbeing measurement literature we present results of a survey, the Social SustainabilitySurvey, alongside a series of indicators aimed at conveying a picture of the subjectiveattitudes of community members in relation to their expressed ideals of sustainabil-ity . In endeavouring to encompass multiple dimensions of sustainability, the indica-tor set is similar to other holistic assessment strategies. However, our approach differsin a number of respects. Firstly, we contrast the orientation of our model with triple- bottom-line approaches, both by revising the underlying structural basis of under-standing sustainability, and by focussing on this understanding from the experientialstandpoint of community participants. In this respect the survey shares commonfeatures with the psychometric perspectives of the Australian Unity Wellbeing Index



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(Cummins et al. 2003 ), World Values Survey (Inglehart and Basanez 2000 ) andWorld Database of Happiness (Veenhoven 2009 ), and indeed certain constructs of the Wellbeing Index and World Values Survey are incorporated into our indicator set.Secondly, we distinguish our approach from purely psychometric studies in focussing

on the community as a level of analysis. Hence, although individuals responsesconcerning their own wellbeing are relevant, we also measure attitudinal assessment of the communities they belong to, reflecting Sirgy s observation ( 2010 ) that com-munity is both equal to and more than the sum of its parts. Finally, we differentiateour approach by looking to measure the intersubjective and future character of a community how members of that community not only feel about themselves in the present, but also about their broader social and natural environment, and about thefuture prospects of that environment.

Methodology

The Social Sustainability Survey was first developed and administered to a number of rural and urban communities in Victoria, Australia in 2006. Over the next 4 years it was further administered to a number of diverse communities in the Southeast Asian,South Asian and Middle Eastern regions. When administered in urban and regionalcommunity settings in India and Sri Lanka, the questionnaires were used asauxiliaries to interviews and consultations with coastal rural communities affected

by the 2004 Indian Ocean tsunami. Use of the questionnaire with the City of Melbourne cohort was through a combination of randomized street and online polling. In all other cases, questionnaires were administered as part of communityconsultation, and participants were selected through a combination of purposive andsnowball sampling in those areas. In those cases, the questionnaire accompanied a more extensive qualitative engagement in the communities sampled, through a seriesof ethnographic, interview-based and observational inquiries into community wellbeing and sustainability (see, for example, Mulligan and Shaw 2007 ; Scerri et al.2009 ). Hence the initial aim of the questionnaire was to supplement existing quali-tative research, to identify areas of community concern, rather than to offer a basis for comparative assessment. Consistent with this aim, a number of supplementary ques-tions were included in different community settings, regional, localized, project- based and time-based differences. For example, questionnaires administered in SriLanka and India after the tsunami included a module of additional questions ondisaster recovery (Mulligan and Shaw 2007 ). A core set of variables was measuredconsistently throughout, with the notable exception of the City of Melbourne ques-tionnaire administered in 2009. These are discussed further below.

The questionnaire is developed on a theoretical model, the Circles of Sustainability ,elaborated in earlier work (Scerri and James 2010a , b). This model departs fromconceptions such as the triple bottom line by treating sustainability under a broadlysocial constructionist and critical pragmatic paradigm. In this model, sustainabilityindicators measure the extent to which a community s goals, desires and ambitionsare being met. Accordingly, in contrast to triple bottom line, we treat the social as anoverall category that is integral to the very definition of sustainability. We thendifferentiate four rather than three conceptual domains economy, ecology , politics ,

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and culture against which the sustainability of different forms of social practice andmeaning can be assessed. Notably, in distinction to the triple bottom line, politics andculture are distinguished as two separate domains of social life that, governed by their own integral logics, warrant equal consideration and assessment as existing in a

relationship with the forms of social life that appear to take place when regarded interms of the economic and/or ecological domains . Aside from representing a moreevenly weighted conceptualization, this approach also mitigates against a key line of critique of the triple bottom line approach the invariable encroachment of economicrelations, especially market relations, upon environmental and social concerns.Instead, respondents perceptions of what counts as indicators of sustainable socialrelations, that is, economic, ecological, cultural and political relations, are treated as prerequisites for sustainability.

The variables we introduce in the questionnaire aim to measure such perceptions

of community sustainability in each of these four domains

both in absolute andrelative, atomistic and holistic, present and future and top down and bottom upterms. As the theoretical model itself was being developed during the pilot of thequestionnaire, we have constructed retrospective proxy subscales to measure sustain-ability against these domains. One side-effect of this iterative process has been someearly obfuscation between economic and ecological variables, and we opted tocollapse these into a single subscale in our principal component analysis below. Wealso constructed a HDI Proxy subscale modelled on the Human Development Index(Human Development Report 2010 ), to examine how our results could be interpreted

against a standardized index, and to test construct validity against the UNDP pub-lished HDI figures. Similarly, in line with our views that community sustainabilitycan be treated as an extension of community wellbeing, we adopted a number of variables from the Wellbeing Index (Cummins et al. 2003 ). Other variables, as part of the core set, were chosen to reflect broader intersubjective and future-orientedcommunity attitudes. The remaining common survey questions capture administra-tive and demographic variables. The complete set of questions and the manifest variables they are measure are listed in Table 2 below.

A further interest was in how well our results at a community level, and measuringsubjective attitudinal responses, could be compared with nation-level objective indi-ces such as the Human Development Index (Human Development Report 2010 ).Though previous research suggests subjective and objective indicators do not alwayscorrelate strongly even under controlled circumstances (McCrea et al. 2006 ), a positive correlation for the self-assessment subscale of the questionnaire acrossdifferent communities is at least suggestive of construct validity. Similarly, we alsodiscussed results with researchers engaged in qualitative research with the surveyedcommunities, to establish anecdotally whether results are consistent with their findings.

Given that the administration of the questionnaire typically took place in thecontext of a range of very different community engagements, where often the verynotion of community was difficult to define, there are notable inconsistencies in thesize and sampling strategies of the samples collected. We also note in our analysis that this is the first time a comparative study of the samples has been conducted. Inaddition to several difficulties harmonizing variant data sets, we became aware of several problems of construct validity and reliability, which we aim to address in



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future iterations of the questionnaire. Nonetheless, the exploratory analysis whichfollows demonstrates how further iterations might complement a sustainability asses-sor s existing toolkit. The analysis also makes a contribution in its own right intounderstanding key factors and relationships of the sampled communities.

The particular countries, sites, communities, years and sample sizes of surveysconducted are listed in Table 1.

Data Preparation and Analysis

The data was collected, recorded and coded into separate SPSS files after eachadministration of the questionnaire. In mid-2010, we began an intensive effort tocollate, clean and consolidate the various data sets. During this process, we encoun-tered several difficulties with both the data and constructs being measured. We outline

the procedure used to prepare and analyse the data, as well as some of thesedifficulties, where they relate to our findings and interpretations below.

To prepare the data for analysis, results of all surveys were consolidated from a number of SPSS and Excel sources into a single SPSS file. A number of operationswere then undertaken to correct for consistency issues described above. These stepsincluded:

1. Coding was re-applied to variables consistently. Where variables had different levels of information (for example, where a combination of ten-point and five- point scales had been used), the lesser of the two options was adopted.

2. Variable and data types were specified for all variables. The majority wereattitudinal variables measured by five-point Likert items; these were accordinglycoded as ordinal .

3. Missing values were flagged explicitly either as user missing or systemmissing .

4. Variable names and labels were made less ambiguous.5. Values were cross-checked across all surveyed communities, to ensure broadly

comparable range, median and frequency distribution values.

Once the data was aggregated in SPSS, a set of core variables was defined. Theseare presented in Table 2, and include those variables common to most of the surveysadministered. Where a given item was not included in a particular survey, values were

Table 1 Countries, years, samplesizes and percentages

Country Year Size (N) Percent

Papua New Guinea 2006 1,062 31.5

Malaysia 2006 105 3.1

Sri Lanka 2007 2008 515 15.3

India 2008 181 5.4

Timor Leste 2008 615 18.3

Israel 2009 137 4.1

Australia 2006 2009 753 22.4

Total 3,368 100.0

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recorded as missing. For the purpose of the exploratory analysis, all Likert items arehere treated as ordinal variable types.

A series of descriptive statistics were obtained for this variable set, both toobserve tendencies in the data and to cross check the data-cleaning process, toensure absence of out-of-band data. We also correlated pair-wise all scalar variables. We then conducted a factor analysis with varimax rotation, to viewwhether variables clustered together intelligibly. We hypothesized also that characteristic demographic data could be useful predictors for some of the behavioural and attitudinal data, and ran regression tests to test this. Finally,ANOVA and further correlation tests were administered to determine whether

Table 2 Sustainability measures, common variables

Variable Domain Variable kind Variable type

Age Demography Characteristic Interval

Gender Demography Characteristic Nominal

Ethnicity Demography Characteristic Nominal

Location Demography Characteristic Nominal

Postcode Demography Characteristic Nominal

Country Demography Characteristic Nominal

Living_With Demography Characteristic Nominal

Household_Size Demography Characteristic Ratio

Country_of_Birth Demography Characteristic Nominal

Years_lived_in_current_neighbourhood Demography Characteristic Ratio

Years_lived_in_previous_neighbourhood Demography Characteristic Ratio

Financial_Assessment Economy Characteristic Ordinal

Health_Assessment Culture Characteristic Ordinal

Level_of_Education Culture Characteristic Ordinal

Identified_Community Culture Characteristic Nominal

Integration_with_Community Culture Attitude Ordinal

Environmental_Conditions Ecology Attitude Ordinal

Life_as_a_Whole Culture Attitude Ordinal

Personal_Relationships Culture Attitude OrdinalSense_of_Safety Culture Attitude Ordinal

Work_Life_Balance Economy Attitude Ordinal

Influence_Authority Politics Attitude Ordinal

Decisions_in_Interest_of_Whole_Community Politics Attitude Ordinal

Experts_can_be_trusted Politics Attitude Ordinal

Govt_make_good_laws Politics Attitude Ordinal

Enjoy_meeting_others_with_differences Politics Attitude Ordinal

Trustworthiness_of_others Culture Attitude Ordinal

Influence_of_cultural_history Culture Attitude OrdinalImportance_of_technology Culture Attitude Ordinal

Frequency_of_use_of_technology Culture Behaviour Ordinal



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meaningful differences existed, for the core attitudinal variables, between thevarious communities participating in the survey, and also how strongly our ownmeasures correlate with published HDI figures. The interpretation of these testsis discussed below.

Findings

After the data was consolidated, our total sample size was 3,368. Country distributionwas heavily oriented towards Papua New Guinea, Australia, East Timor and SriLanka. Gender distribution was approximately even (Female 0 49.4%; Male 0

50.2%), while age distribution is skewed towards a younger demographic, with over 75% of respondents under the age of 50. Self-assessments of health, wealth and

education

variables related to indices such as the HDI

reflect the application of the survey to large number of Global South countries. The majority of respondentsdescribed themselves financially as Struggling (50%), with only 9.1% stating theywere Well-off . 45.2% of respondents stated they had primary school or no formaleducation at all, while only 18.4% had completed secondary school. Conversely,against the health measurement-construct, 48.6% of respondents self-assessed as myhealth is generally good .

A proxy HDI index variable, termed HDI Self-Assessment was composed out of the normalized values of health, financial and education self-assessment variables.

The frequency distribution of this composite variable demonstrates that in fact therelative skews of these variables collectively cancel out, leaving a close approxima-tion to a normal distribution, as shown in Fig. 1 below.

Of the 15 common attitudinal variables listed in Table 2, all but three hadmedian, and all but one had mode values of Agree (4). As all Likert items were phrased in such a way that agreement tended to endorse the underlying variable being measured, this indicates a degree of correlation between responses islikely. The average mean value was 3.65, while the average standard deviationwas 1.06, a relatively low dispersion, one that confirms the clustering of responses on the positive end of the scale. As the presentation of inferentialtests below suggests, there are some interesting differences between communitiessampled however.

Correlations

Both Spearman s rho and Pearson s correlation coefficient were obtained of all corescalar variables, 22 in total, and separately, of all attitudinal variables, 15 in total. Of 231 possible scalar correlations, 179 (77.5%) were significant at the 0.01 level, with a further eight significant at the 0.05 level (81.0%). Of the 105 possible correlations of the 15 attitudinal variables, 100 were significant at the 0.01 level. Together theseresults suggest a very high degree of dependence between the variables, a featurediscussed further below in both the factor analysis and survey redesign sections.Given the sample size, use of five-point scales for attitudinal variables, and potentialfor skew in both wording of question probes and sampling strategy, such coalescenceis perhaps not surprising.

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Principal Component Analysis

A factor analysis was conducted on all attitudinal variables. Kaiser-Meyer-Olkinmeasure of sampling adequacy was 0.843, a very high level for conducting factor analysis (Field 2005 ). Varimax rotation was selected, due to potential dependencies between discovered factors (Field 2005 ). Table 3 tabulates the varimax-rotatedfactors, with the factors themselves interpolated as follows:& Satisfaction with various aspects we have interpreted against our theoretical four-

domain model as economic and ecological conditions (life as a whole, involve-ment with community, personal relationships, the environment, sense of safety,work/life balance).

& Trust and confidence in political conditions (ability to influence authority, belief decisions are in interest of whole community, trust in experts and government)

& Trust and confidence in cultural conditions (enjoy meeting and trust in others,influence of history, importance and use of technology)

Fig. 1 Distribution of HDI self-assessment variables



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The three factors are interpreted here as accounting for each of the four domains in theunderlying model. The first factor combines all six satisfaction constructs, taken fromthe Australian Unity Wellbeing Index (Cummins et al. 2003 ). These have been

admittedly quite liberally interpreted as reflecting general contentment witheconomic and ecological circumstances, where ecology is considered as the inter-section between the social and natural context. The following two factors moredirectly aggregate items reflecting political and cultural engagement, respectively.

Since missing values caused a large number of cases (1,593, or 47.3% of 3,368) to be ignored in the analysis, a separate analysis was conducted with mean valuessubstituted back in. The analysis showed a weaker sampling adequacy result, but no change in the variables or factors identified. A series of composite indices, termedrespectively Attitudes towards Economy and Ecology , Attitudes towards Politics and Attitudes towards Culture , was constructed from the normalized values of the relevant underlying indicators. These in turn were compiled into an overall Attitudinal Self- Assessment index, similar to the HDI Self-Assessment variable described above. Allfive computed variables were then used in subsequent regression and ANOVA tests.

Predicting Sustainability Assessments Regression Results

Regression tests were conducted to note the significance and direction of relation-ships between the principal component clusters of attitudinal variables, and demo-graphic and self-assessment characteristics. Results of these for all attitudinalvariables are included in Table 4. For the Well-being Index satisfaction levels(interpreted, as suggested above, so as to cover economic and ecological domains),

Table 3 Principal component analysis

Component 1 Component 2 Component 3

Integration_with_Community .639

Environmental_Conditions .674

Life_as_a_Whole .711

Personal_Relationships .669

Sense_of_Safety .627

Work_Life_Balance .629

Influence_Authority .577

Decisions_in_Interest_of_Whole_Community .711

Experts_can_be_trusted .765

Govt_make_good_laws .731

Enjoy_meeting_others_with_differences .581

Trustworthiness_of_others .551

Influence_of_cultural_history .488

Importance_of_technology .577

Frequency_of_use_of_technology .671

Principal component analysis is used as the extraction method. Rotation is conducted using varimax withKaiser normalization, converging in 5 iterations. Only scores above 0.4 are recorded

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and attitudes relating to the political domain, only the financial self-assessment variable stands out as a strong and negative predictor, suggesting that those whoassess themselves poorly nonetheless score highly against satisfaction and politicalengagement indicators. Conversely, all variables other than Financial Assessment

and Years lived in previous neighbourhood have a strong predictive relationship onthe aggregated cultural engagement indicator.

Comparing Communities ANOVA and Correlation Results

An ANOVA test was also conducted using the community as the grouping variable. Of particular interest was whether the first three principal components identified in thecomponent analysis had significant differences between communities. Similarly weexamined the composite Attitudinal Self-Assessment and HDI Self-Assessment

variables across the groups. The tabulated results of this test are included in Table 5.Each of the five computed variables showed significant differences across thedifferent community groups at both 0.05 and 0.01 levels.

Table 6 compares both mean values and rank for the five composite variablesacross each of the seven communities (Melbourne (2009) and Timor Leste areincomplete due to certain items not being included in their respective surveys). Asthe ranks make clear, HDI self-assessment means appears to correlate with attitudestowards economy, ecology and culture, with Australian Towns and Be er Sheva

ranking highly for each of these four variables. Attitudes towards Politics , on thecontrary, correlate inversely. This suggest that communities generally satisfied andconfident regarding economic, ecological and cultural dimensions are sceptical of prevailing power systems and structures; those, on the other hand, who self-assess poorly and are dissatisfied with present material conditions nonetheless expressgreater trust and confidence in political mechanisms.

A further pair-wise set of correlations was ran over the composite variables, whichconfirm the above findings across the whole data set all variables correlate signifi-cantly at 0.05, 0.01 and 0.001 levels, with Attitudes towards Politics the only variablecorrelating negatively with the others. We also plotted our HDI Self-assessment proxy

Table 4 Regressions

Model Unstandardizedcoefficients

Standardized coefficients t Sig.

B Std. Error Beta

(Constant) 81.237 2.084 38.979 .000

Age .612 .220 .089 2.781 .006

Household size .159 .119 .043 1.336 .182Financial assessment 2.649 .536 .155 4.946 .000Health assessment .606 .502 .039 1.206 .228Level of education .263 .272 .031 .966 .334Years lived in current neighbourhood .812 .220 .124 3.687 .000

Years lived in previous neighbourhood .198 .167 .039 1.189 .235



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variable against 2010 HDI values given by the UNDP for the corresponding countries.

Here we noted a strong positive correlation ( R0

0.756, p< 0.05).

Discussion

In the first instance, this article has reflected our interest in examining whether a generalizable questionnaire could accurately measure subjective attitudes of members across diverse sites and communities, and supplement informationavailable from other sources. For this purpose we used two forms of control:the ethnographic research conducted at the communities, and general HDI statisticsfor the countries in which the communities reside. Secondly, we investigatedwhether salient differences existed between low and high-income communitiestowards different sustainability dimensions. In the context of the communitiessurveyed here, these point to distinctions between communities in the Global Northversus the South. Finally, the questionnaire is based upon an alternative theoreticalconception of sustainability to the common triple bottom line paradigm. We thereforeused the questionnaire as a form of extended pilot, during which this conception wasfurther developed, and in turn led to a reformulation of the questionnaire itself, which we present below.

Overall, results suggest that the questionnaire provides a useful and generalinstrument for measuring community attitudes towards what is perceived bycommunity members to constitute sustainability . Administered over a broadrange of communities urban and rural, high and low-income, and those dealingwith the aftermath of environmental (Sri Lanka), political (Timor Leste) andeconomic (Melbourne) upheaval post facto regressions and component analyses

Table 5 ANOVA of composite variables across communities

Sum of squares df Mean square F Sig.

Attitudes towards economyand ecology

Between Groups 1763.205 4 440.801 27.496 .000

Within Groups 34612.283 2159 16.032

Total 36375.488 2163

Attitudes towards politics Between Groups 1999.909 5 399.982 40.061 .000

Within Groups 26098.794 2614 9.984

Total 28098.704 2619

Attitudes towards culture Between Groups 14879.615 5 2975.923 305.189 .000

Within Groups 26435.147 2711 9.751

Total 41314.762 2716

Attitudinal self-assessment Between Groups 6620.378 4 1655.095 14.719 .000

Within Groups 199032.075 1770 112.448

Total 205652.453 1774

HDI Self-assessment Between Groups 429736.973 6 71622.829 204.563 .000

Within Groups 1122152.037 3205 350.125

Total 1551889.010 3211

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T a

b l e 6

C o m p o s i t e v a r i a b l e m e a n c o m p a r i s o n

M e a n v a l u e s

V a l u e s

A t t i t u d e s t o w a r d s E c o n o m y

a n d E c o l o g y

A t t i t u d e s t o w a r d s

P o l i t i c s


C u l t u r e

A t t i t u d i n a l S e l f - A s s e s s m e n t H D I S e l f - A s s e s s m e n t 2 0 1 0 H D I C o u n t r y V a l u e s

a

A u s t r a l i a n T o w n s

2 4 . 2

1 1 . 5

2 1 . 4

7 2 . 8

6 5 . 5

0 . 9 3 7

B e e r S h e v a , I s r a e l

2 4 . 3

1 1 . 7

2 2 . 7

7 4 . 8

7 8 . 4

0 . 8 7 2

M a l a y s i a

2 1 . 4

1 3 . 1

1 5 . 8

6 5 . 2

4 6 . 5

0 . 7 4 4

M e l b o u r n e , A

u s t r a l i a

.

.

.

.

5 3 . 6

0 . 9 3 7

P a p u a N e w G u i n e a

2 4 . 2

1 3 . 8

1 7 . 1

7 0 . 9

4 1 . 6

0 . 4 3 1

S r i L a n k a

2 2 . 5

1 3 . 5

1 9 . 7

7 2 . 7

3 8 . 4

0 . 6 5 8

T i m o r L e s t e

.

1 4 . 0

1 5 . 3

.

3 6 . 0

0 . 5 0 2

M e a n r a n k s

A t t i t u d e s t o w a r d s E c o n o m y

a n d E c o l o g y


P o l i t i c s


C u l t u r e

A t t i t u d i n a l S e l f - A s s e s s m e n t H D I S e l f - A s s e s s m e n t 2 0 1 0 H D I C o u n t r y R e l a t i v e

R a n k s

a

A u s t r a l i a n T o w n s

3

6

2

2

2

1

B e e r S h e v a

1

5

1

1

1

2

M a l a y s i a

5

4

5

5

4

3

M e l b o u r n e , A

u s t r a l i a

3

1

P a p u a N e w G u i n e a

2

2

4

4

5

7

S r i L a n k a

4

3

3

3

6

5

T i m o r L e s t e

1

6

7

6

a

( H u m a n D e v e l o p m e n t R e p o r t 2 0 1 0 )



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demonstrate moderately coherent patterns. Such patterns are commensurate withwhat the theoretical model suggests is the case: that sustainability combinesabsolute and relative subjective interpretations of prospects for individual andcollective wellbeing, now and into the future, and requires input both by

community members and authorities. The strong correlation result between our proxy HDI variable and actual HDI figures suggests both reasonable construct validity and high convergence between the subjective impressions and objectiveassessments among the communities sampled. This is particularly striking due totwo potentially confounding elements during the periods examined. The Mel- bourne survey was conducted in 2009, at the height of concerns over the GlobalFinancial Crisis, while the Sri Lanka survey was conducted relatively soon after,and in areas directly affected by, the tsunami in 2004. The survey results alsoconfirmed data obtained from observations and interviews. Studies of affected

communities in post-tsunami in Sri Lanka by Mulligan and Shaw ( 2007 ), for example, outline both the immense development challenges facing communities, andtheir resilient attitudes in response.

While the aims of the survey were exploratory and emphatically not intended tointroduce ranking considerations the correlation, regression and ANOVA tests alsodo demonstrate significant relationships and high degrees of deviance between thevarious communities who have participated. The key finding from the explorationappears to be the inverse relationship between levels of political engagement andsatisfaction and all other subjective indicators economic, ecological and cultural.

Results for Australian and Israeli communities, in particular, demonstrate that thosewith high levels of general satisfaction, education and material contentment tend to bemore sceptical and pessimistic with regard to their involvement in structures of power. This clearly needs more robust study but points to a potential series of hypotheses to be tested in future rounds of the survey, and possibly calls for morerobust theorization of the links between education, material contentment and ideals of political wellbeing.

From the point of view of establishing the theoretical model, of greatest interest in the results was the strong relationship between the first three factorsof the factor analysis, and the four domains economic, ecological, politicaland cultural articulated in the theoretical model. This suggests that the surveyinstrument successfully measures community values are oriented towards different domains of sustainability : that is, sustainability is a social problem that encom- passes economic, ecological, political and cultural relations, relations that are bothreproduced in social structures but also open to pressure to change from social agentsor actors.

This said, several confounds should be noted. Firstly, these factors all onlyaccount for 47.2% of the total variation leaving a large amount of attitudinalvariance still unexplained by the four-domain model. Secondly, the limitationsaround the survey design and administration discussed earlier suggest higher levels of significance testing are needed at the very least before results can beinferred to the broader community populations. Thirdly, both economic andecological constructs were coalesced in the primary factor identified. Given a key claim of the four-domain model is that each of the domains is at least potentially in conflict with others, the moderate sample size and range of

L. Magee et al.


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communities ought to bring out greater variation between constructs measuringeach domain. Of course both the domain-construct relationship and the factor analysis have been conducted ex post ; an important feature to exhibit in results of follow-up surveys would be a stronger correlation between ex ante and ex post

alignment of variables to co-ordinating factors. Nevertheless, the coalescence of principal components with the independently derived domains suggests theseremain a sound basis for the construction of future iterations of any resultingindicator set.

Measuring Social Sustainability, Version 2.0

As mentioned above, a range of difficulties were encountered with the data andtheir analysis. In part this is due to the initial aims of the questionnaire, which

were to illustrate local areas of community concern, rather than to coerce com-mensurability across all applications of the questionnaire. Other issues relate tospecific applications of the questionnaire reliable translations of key constructs,inconsistent coding and varied sampling strategies employed and these clearlylimit the inferential power of the results. More generally, a more systematicorganization of items and scales would improve the reliability and validity of results from future applications of the instrument.

To address these goals, we conducted a number of workshops in 2010 and 2011. Arevised set of indicators/questions was drafted, with an associated set of reference

questions and responses. These retained consonance with the existing survey yet sought to address the identified limitations. Version 2.0 now measures sustainabilityexplicitly against the four domains and their subdomains, which only formed the background to the original survey. More explicitly, community sustainability isassessed with reference to the following:

& Economic prosperity the extent to which the community can engage in activitiesrelevant to their economic wellbeing and feel confident about the consequence of changing structures beyond their locale.

& Ecological resilience the extent to respondents perceive the rates at which thesurrounding natural environment can withstand and recover from the community sactions.

& Political engagement the extent to which members of the community can participate and collaborate in structures and processes of power that affect them.

& Cultural vitality the extent to which the community is able to maintain anddevelop its beliefs, celebrate its practices and rituals, and cultivate narratives of meaning that define the community.

In total, the revised structure of 48 variables more closely measures com-munity sustainability against our own Circles of Sustainability theoretical model.We have included eight items for each of the four domains, along with 10 demo-graphic and six wellbeing items (the latter are again sourced from the AustralianUnity Wellbeing Index). The domain items are further divided into subscales for sense of trust , concern and optimism about the future . We have also mapped thequestions in the survey in relation to the Human Development (Creating Capabilities)approach (Nussbaum 2011 ), to provide more structured concordance with an existing



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widespread measure of sustainability. We plan to conduct further pilot studies of theinstrument in 2012.

Conclusion

The Community Sustainability Survey has been applied to approximately 3,300members of various communities in the Middle East, South and Southeast Asia between 2006 and 2010. Our results showed several interesting patterns: membersof communities in countries with above average HDI scores ( Australian towns , Be er Sheva , Melbourne ) scored higher on all but one of our composite attitudinalscales (attitudes towards economy, ecology, culture, self-assessment and HDI proxy).The exception, Attitudes towards Politics , tentatively corroborates other findings

confirming widespread disaffection with politics in economically advanced liberaldemocracies, such as those observed over several decades by Inglehart ( 1977 , 1990 ,1997 ). The relative stable political environments in these countries further suggestsdiscrepancies between subjective assessments and objective conditions regardingspecifically political sustainability. As we acknowledge though, this result may bethe product of confounding variables and construct validity. Political scepticism canequally be taken as an indicator of a robust political environment rather than itsconverse, the failure of political processes. We also found a pleasing degree of correlation between our own HDI proxy variable and published UNDP HDI values,

and anecdotal confirmation with qualitative research conducted at the same communitysites.In terms of the first of four dilemmas we introduced at the outset of this article, we

note this instrument will sit alongside others piloted under the same project rubric, thuscomplementing the standardized, top down indicators of sustainability outlined herewith locally developed, bottom up and issue-based indicators. In terms of the remain-ing three of the dilemmas, the results of the questionnaire provide a useful context for examining the relationship between alternative subjective, intersubjective and objectivemodes of measurement; between individuals and community; and between present wellbeing and future sustainability. The reformulation of variables will, we expect,allow us to better gauge these dimensions, and so provide a more robust instrument for understanding and assessing sustainability from a community s own point of view.

Though initially intended as an augmented instrumental probe into qualitativemodes of community engagement, the process of consolidating, cleaning andanalysing the results of the survey suggests that the instrument has a potentially broader role to play as a tool for assessing a community s own attitudestowards sustainability. Further work is required to formulate and pilot therevised survey. However, as the exploratory analysis shows, useful results have been extracted from the existing data set, including the inverse relations be-tween political and other domain indicators, and a potential scoring mechanismfor ranking communities self-assessments. We suggest that it may fill a gap between the current group of objective, techno-scientific indices, and subjective, psychometrically-oriented well-being and quality of life measures, focussing onsustainability as an intersubjective and future-oriented process between communitymembers.

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Acknowledgements The people who have contributed to the development of this questionnaire are toonumerous to list, but to give a sense of the reach of our indebtedness to others we list the researchers whowere involved in the Papua New Guinea project: Albert Age, Sama Arua, Kelly Donati, Jean Eparo, BenoErepan, Julie Foster-Smith, Betty Gali-Malpo, Andrew Kedu, Max Kep, Leo Kulumbu, Karen Malone,Ronnie Mamia, Lita Mugugia, Martin Mulligan, Yaso Nadarajah, Gibson Oeka, Jalal Paraha, Peter Phipps,

Leonie Rakanangu, Isabel Salatiel, Chris Scanlon, Victoria Stead, Pou Toivita, Kema Vegala, Naup Waup,Mollie Willie, and Joe Yomba. In addition, given the issue that the PNG project involved many languagesacross 50 villages in five provinces, we need to thank in particular, Gerard Arua, Vanapa, Central Province;Monica Arua, Yule Island, Central Province; Viki Avei, Boera, Central Province; Sunema Bagita, Provi-sional Community Development Advisor, Milne Bay Province; Mago Doelegu, Alotau, Milne BayProvince; Clement Dogale, Vanagi, Central Province; Jerry Gomuma, Alepa, Central Province; AlfredKaket, Simbukanam/Tokain, Madang Province; Yat Paol from the Bismark Ramu Group, Madang Prov-ince; Joseph Pulayasi, Omarakana, Milne Bay Province; Bing Sawanga, Yalu, Morobe Province; Alexia Tokau, Kananam, Madang Province; and Naup Waup, Wisini Village, Morobe Province. They became our formal research leaders in their respective locales and guides to language nuances.

Parts of this research were supported under Australian Research Council s Linkage Projects fundingscheme, and for that we thank the ARC.

We also gratefully acknowledge the comments and suggestions of three anonymous reviewers in the preparation of this article.

Appendix 1. Measuring Community Sustainability, Version 2.0

Demographic Variables

1. What is the highest level of formal or school education that you have completed?

[Level of educational attainment]2. What is your age? (Please write how many years old you are.) [Age]3. What is your gender? [Gender]4. Financially speaking, how would you describe your household? [Financial

self-assessment]5. Compared to other people of the same age, how would you describe your

health? [Health self-assessment]6. Have there been times in the past 12 months when you did not enough money

for the health care that you or your family needed? [Cost of health care]

7. With whom do you live? [Cohabitation]8. How many people live in your household presently? [Household size]9. For how many years have you lived in your current locality? (That is, in this

local place or area) [Duration at current location]10. What or whom do you identify as your main community? [Identified

community]

Well-Being Satisfaction Levels

11. How satisfied are you with being part of your community?12. How satisfied are you with the environment where you live?13. How satisfied are you with your personal relationships?14. How satisfied are you with the balance between your work and social life?15. How satisfied are you with how safe you feel?16. How satisfied are you with your life as a whole these days?



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Political

Sense of Trust

17. I can influence people and institutions that have authority in relation to mycommunity.

18. Decisions made in relation to my community are generally made in the interestsof the whole community.

19. Outside experts can be trusted when dealing with local issues.20. Governments make decisions and laws that are good for the way I live locally.

Sense of Concern

21. I am concerned that global levels of politically-motivated violence will affect our locality.

22. I am concerned about the corruption of local political institutions.

Sense of Optimism About the Future

23. Outsiders are and will continue to be comfortable coming to live in our locality.24. People can learn to live with people who are culturally different from

themselves.

Ecological

Sense of Trust

25. Experts will always find a way to solve environmental problems.26. My identity is bound up with the local natural environment and landscape.27. Conserving natural resources is unnecessary because alternatives will always be

found.28. In order to conserve natural diversity, economic development should be excluded

from substantial wilderness areas.

Sense of Concern

29. Across our locality there is good access to places of nature.30. I am concerned that global climate change will affect our locality.

Sense of Optimism About the Future

31. We have a capacity to meet our local needs for basic resources such as food,water and energy.

32. Continuing economic growth is compatible with environmental sustainability.

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Economic

Sense of Trust

33. Wealth is distributed widely enough to allow all people in our locality to enjoy a good standard of living.

34. Our government supports economic growth as one of its highest priorities.35. Our economy is adequately protected against competition from foreign-owned

businesses.36. Hard work and initiative alone is enough to get ahead financially.

Sense of Concern

37. I am concerned that global economic change will affect our locality.38. A slump in the local economy.

Sense of Optimism

39. Keeping our economy sustainable requires that our needs for a wide range of consumer goods are fulfilled.

40. Current levels of consumption in our locality are compatible with an environ-

mentally sustainable future.

Cultural

Sense of Trust

41. I feel that I can influence the generation of meanings and values in relation toour way of life.

42. I feel comfortable meeting and talking with people who are different from me.

43. Most people can be trusted most of the time.44. Places of learning, health, recreation and faith are distributed across our locality

in a way that ensures good access by all.

Sense of Concern

45. I am concerned about a decline in the vitality of local cultural institutions.46. I am concerned that globally-transmitted cultural values will affect our locality.

Sense of Optimism

47. I am free to express my beliefs through meaningful creative activities.48. People living in our locality are free to celebrate publicly their own rituals and

memories, even if those rituals are not part of the mainstream culture.



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Measuring Social Sustainability

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