Cultural Indicators in Abu Dhabi: theoretic framework and challenges for their building
Published in Social Sciences, Statistics, and Law, Politics & International Studies
Recent discussions on the advancement of cultural measurement have demonstrated growing interest in our experience of conceptualizing Abu Dhabi’s pioneering framework for culture data collection and statistics, CultureSTATS-AD project.
Our foundational theoretical paper, published in Quality & Quantity and entitled "Cultural indicators in Abu Dhabi: theoretic framework and challenges for their building" (2021), was focused on adapting the emerging Abu Dhabi cultural indicators to address both (1) comparative international assessments and (2) the specificities of the local cultural ecosystem.
I would like to revisit this aspect, which remains relevant across all statistical levels and central to linking local cultural dynamics with the UN Sustainable Development Goals (SDGs).
The etymology of the term “statistics” traces back to the Latin word “status” (meaning state, condition, estimation, or position). Indeed, the ways we think about culture, act within it, and describe it - especially through statistics - are closely linked to challenges in cultural management, policymaking, monitoring of national trends, and the international harmonization of statistics. However, caution must be exercised to ensure that cultural statistics do not impose a rigid framework that limits the visibility of those cultural activities that are inherently unique to each locality.
Even though meeting international standards - such as UNESCO’s Culture 2030 Indicators Framework - is essential for ensuring global statistical harmonization, a direct replication of foreign best practices in cultural measurement (such as, for example, ESSNet-Culture or other frameworks) is not relevant for Abu Dhabi, as existing cultural practices and data are shaped by Abu Dhabi’s unique historical, administrative, and legislative contexts.
Nonetheless, we saw in 2020 that establishing partial correlations between Abu Dhabi’s taxonomy and international approaches offered a path forward.
Our research addressed this challenge of articulations between the ‘local’ and the ‘global’ by adopting a pragmatic approach to Abu Dhabi’s cultural vocabulary. At first glance, the Abu Dhabi culture vocabulary seems similar to the common international practice. However, the practical usages of culture definitions by policymakers, culture professionals, academics, etc. replicate a myriad of underlying social processes.
The paper proposed a transversal contextual analysis of Abu Dhabi's cultural documentation to recognize these processes as evolving components of the local cultural ecosystem that need to be continuously explored further through qualitative methods. This tailored approach aimed to understand and map the conceptual, legal, and social contexts in which currently used cultural definitions are embedded.
The analysis was based on the assumption that the effectiveness of management tools (e.g., Abu Dhabi’s emerging cultural statistics) lies not in their existence or mere use, but in their capacity to connect to a shared discourse (Detchessahar and Journé, 2007) - such as a cohesive narrative around Abu Dhabi’s cultural ecosystem and relevant policies.
The intertextuality of management tools (Kristeva, 1980) becomes consequently essential, as in this perspective, the reader's comparisons and relationships made with other texts make it possible to construct the meaning of the text read (Riffaterre, 1980). This systemic vision allows for the identification of what needs to be measured through the statistical indicators.
A transversal contextual analysis of Abu Dhabi’s cultural documentation provides an understanding of local cultural processes and the contexts in which key concepts are situated, while helping to establish logical links among the key elements of the policymaking system. Subsequently, our research proposed using these identified contexts as linchpins for developing cultural indicators.
Since Abu Dhabi’s culture-related documentation is still being established, our approach remained exploratory and included both normative texts (e.g., legislation) and other relevant materials, schematically visualized below. Based on this analysis, we designed a strategy for indicator selection, definition, and data population.
To conceptualize the relationship between Abu Dhabi's specific and broader international cultural statistics, we used Cartwright’s (2012) notions of “causal factors” and “support factors”, applied to the background conditions of the cultural phenomena to be measured. These factors vary significantly by local context, even when the resulting indicators appear internationally comparable.
In other words, the rationale behind evidence-based policymaking relies on proven causal links between a policy intervention and the statistically verified fact that it worked in a particular context. However, the success of such policies in one setting does not straightforwardly support the conclusion that they will be effective in the context of Abu Dhabi (and vice versa). Our methodology, therefore, linked cultural policy definitions - often broad and vague - with the specific local realities of their implementation.
In this sense, the development of cultural indicators contributes to an inductive reconstruction of cultural policy scope. It helps clarify the values and principles underpinning the sector. As statistics strive for pragmatic connections with reality, their precision is a relative value: an imperfect evaluation tool is better than no framework at all. Even if an indicator reflects indirect or partial representations of a phenomenon, it can still improve its effectiveness in conveying useful insights. This underscores the crucial role of indicators in the policy cycle, as data continually reshape our understanding of culture and the challenges facing cultural policy.
However, our approach cannot be considered exhaustive and faced several limitations. We demonstrated that a vocabulary-based method is effective in revealing both local concerns and opportunities for international comparability in cultural statistics. Nonetheless, we have not yet presented a full framework for bottom-up cultural indicator development. Since 2020, extensive qualitative culture research and data collection have been performed in Abu Dhabi, supporting the sustainable development of the emirate’s cultural statistics system.
References
Cartwright, N., & Hardie, J. (2012). Evidence-based policy: A practical guide to doing it better. Oxford University Press.
Detchessahar, M., & Journé, B. (2007). Une approche narrative des outils de gestion. Revue Française de Gestion, 174(5), 77–92.
Kristeva, J. (1980). Desire in language: A semiotic approach to literature and art. Columbia University Press.
Raevskikh, E., Di Mauro, G., & Jaffré, M. (2024). From living heritage values to value-based policymaking: Exploring new indicators for Abu Dhabi’s sustainable development. Humanities and Social Sciences Communications, 11, Article 1311. https://doi.org/10.1057/s41599-024-03841-5
Raevskikh, E., & Di Mauro, G. (2025, April 11). Rethinking cultural indicators as a lever for sustainable development: Insights from the Culture Summit Abu Dhabi 2025. Springer Research Communities Blog. https://communities.springernature.com/posts/rethinking-cultural-indicators-as-a-lever-for-sustainable-development-insights-from-the-culture-summit-abu-dhabi-2025
Raevskikh, E., Haidar, R. O., & Alkhamis, N. (2021). Cultural indicators in Abu Dhabi: Theoretic framework and challenges for their building. Quality & Quantity, 55(6), 2065–2086. https://doi.org/10.1007/s11135-020-01090-7
Riffaterre, M. (2005). La trace de l’intertexte. La Pensée, 215, 4–18.
🟣 I am a Russian-French scholar and research leader with over a decade of international experience across public, academic, and multilateral settings. I am passionate about bringing bold ideas to life and always open to connecting and exchanging ideas on visionary projects — whether related to culture or beyond.
🇦🇪 Current Role
Since 2019, I have served as Head of the Research and Analysis Unit at the Department of Culture and Tourism – Abu Dhabi, leading CultureSTATS-AD, the MENA region’s pioneering culture research program.
Key achievements:
• Published 20+ research reports supporting Abu Dhabi’s culture sector decision-making — recognized by the UAE National Library as part of the country's intellectual heritage (2025)
• Authored academic articles in Quality and Quantity (2021) and Nature (2024), ranked among the top 10% (94th percentile) of research outputs ever tracked by Altmetric
• Launched the biennial Abu Dhabi Culture Population Survey
• Developed the region’s first Register of Cultural Organizations and Professionals
• Established baselines for Abu Dhabi’s international cultural rankings
• Collaborated with UNESCO, IFACCA, WCCF, ENCATC, OECD, and the Mori Memorial Foundation on a range of initiatives
• Designed the CultureSTATS-AD concept from the ground up; oversaw HR, Finance, and Procurement processes
💼 Previous Roles
• Research Fellow, National Centre for Scientific Research (CNRS), France (2015)
• Post-doctoral Researcher, University of Avignon, France (2014)
• Lecturer, School for Advanced Studies in the Social Sciences (EHESS), France (2013)
• Visiting Researcher in Italy, Sweden, and Poland
✍️ Contributions and editorial engagements
• Contributor: World Economic Forum, Springer Nature Research Communities, ET Edge Insights (India)
• Reviewer: Quality and Quantity: International Journal of Methodology (Q1); Humanities and Social Sciences Communications (Q1)
📚 Education
• PhD in Sociology, School for Advanced Studies in the Social Sciences (EHESS), Paris, 2014
• Specialist in Public International Law, Moscow State University, 2009
🌍 Affiliations
• Member, Academic Advisory Board, IAFOR (Japan)
• Visiting Lecturer & Associate Researcher, IIM Rohtak (India)
• Fellow, Royal Society of Arts (RSA)
Follow the Topic
-
Quality & Quantity
This journal constitutes a point of reference for European and non-European scholars to discuss instruments of methodology for more rigorous scientific results in the social sciences.
Related Collections
With Collections, you can get published faster and increase your visibility.
Statistics and Data Science for Evaluation and Quality
Call for Papers
Following the objectives of the "12th Scientific Meeting organized by the Statistics for the Evaluation and Quality of Services Group of the Italian Statistical Society SVQS" (https://ies2025.sis-statistica.it) to be held in Bressanone, Italy, on June 25-27, 2025, this Special Issue titled "Statistics and Data Science for Evaluation and Quality" invites research contributions concerning the statistical evaluation of both private and public services.
As industries and organizations increasingly rely on data-driven decision-making, the integration of advanced statistical techniques and data science becomes essential for ensuring robust evaluation processes and maintaining high standards of quality. The proposed Special Issue aims to explore the critical role of statistical methods and data science in the evaluation and enhancement of quality across various domains and to provide a comprehensive overview of how statistics and data science are transforming the landscape of quality evaluation and offer insights into future trends in this dynamic field.
"Statistics and Data Science for Evaluation and Quality" invites contributions that showcase innovative applications of statistical methodologies, machine learning, and data analytics in the assessment of quality in sectors such as healthcare, education, manufacturing, and services. Emphasis is placed on multidisciplinary approaches that exploit modern data science tools to address complex evaluation challenges.
Papers highlighting case studies, methodological advancements, and novel frameworks that improve the reliability, validity, and effectiveness of quality assessments are particularly welcome.
The subject matters of the contributions cover the following thematic areas (but are not limited to):
• Digital transition
• Official statistics
• E-commerce and digital marketing
• Public administration
• Enterprises
• Food and wine
• Environment and territory
• School, education and training
• Healthcare and wellness
• Finance, bank and FinTech
• Sports
• Justice System
• Sustainability
• Labour market
• Tourism
• Well-being and welfare
• Transport
• University and research
Papers should be submitted via the journal’s online submission system available through the journal homepage here
When submitting please choose the special issue: “Statistics and Data Science for Evaluation and Quality” as the article type from the drop-down menu.
All papers must follow the guidelines outlined by the journal for submission, available at: Submission guidelines
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.
For any questions, interested authors can contact the guest editors.
Kuniyoshi Hayashi, hayashikuni@kyoto-wu.ac.jp
Christophe Ley- christophe.ley@uni.lu
Amalia Vanacore - amalia.vanacore@unina.it
Publishing Model: Hybrid
Deadline: Dec 31, 2025
AI-Driven Innovation and Multi-Sector Collaborations for Sustainable and Urban Development
In line with the objectives of the international conference "Sustainable and Socially Responsible Development in the Network of Socioeconomic Relations: The Triple Helix for Sustainable Development," held in Gdansk, Poland, in June 2024, this Special Issue invites contributions that apply qualitative, quantitative, and mix-methods research to explore cutting-edge developments in sustainable urban and socioeconomic development.
This Special Issue, titled "AI-Driven Innovation and Multi-Sector Collaborations for Sustainable and Urban Development,” will focus on the intersection of artificial intelligence, public-private-university partnerships, and sustainable development practices in urban settings. By emphasizing these critical areas, the issue will explore how AI-driven innovative technologies, policy frameworks, and collaborative models can address the complex challenges of sustainable development, particularly in urban settings.
The proposed Special Issue distinguishes itself by incorporating AI as a critical driver of change in sustainability practices that improve agglomeration functioning. Contributions are encouraged to cover a wide range of topics that explore the transformative potential of AI in promoting sustainability, optimizing urban systems, fostering labor market adaptations, and creating synergies between different sectors for a greener and more equitable future.
It aims to attract diverse submissions, including empirical studies, case studies, contributions to methodology, and policy analysis. Key areas of focus will include, but are not limited to:
• AI in Sustainable Urban Systems: Exploring how AI-driven technologies are reshaping urban environments, optimizing transport networks, and enhancing resource efficiency, particularly in smart cities and sustainable mobility, addressing the challenges and opportunities of sustainable urban planning, focusing on integrating green technologies, promoting resilient infrastructure, and ensuring equitable access to resources.
•AI and Triple Helix for Sustainable Development: Analyzing the role of public-private-university partnerships in AI-driven innovation, particularly in sustainability-related areas such as environmental management, urban planning, business models, and economic development. Contributions can examine case studies, collaboration models, and policy frameworks promoting multi-sectoral cooperation.
•AI, Social Innovation and Sustainable Solutions: Investigating new approaches to fostering social innovation in the context of sustainable development. Topics may include innovative AI-driven solutions for urban challenges, community-driven development, and city social responsibility initiatives.
•International Triple-Helix Cooperation for Sustainable Development: Examining global public-private-university collaborations and policy frameworks that support implementing sustainable development goals (SDGs) across different regions and sectors.
This Special Issue will offer academics, policymakers, and industry professionals a platform to present novel insights, engage in meaningful discussions, and explore actionable strategies and business models for advancing sustainable development through AI-driven innovation and multi-partner collaboration. By gathering diverse perspectives and cutting-edge research, this issue aims to contribute to a deeper understanding of the complex interactions between technology, policy, and sustainability, providing solutions for a more resilient and sustainable future.
To ensure the robustness and relevance of contributions, the Special Issue places a strong emphasis on the methodological rigor and diversity of approaches. We invite submissions employing:
1. Quantitative Research: Contributions using advanced AI-based models, algorithms, and tools for predictive analysis, classification, or clustering tasks in urban and socioeconomic contexts. This includes large-scale data analyses, machine learning applications, and econometric modeling to uncover patterns and trends in sustainability and urban development.
2. Qualitative Research: Studies exploring policy frameworks, case studies, and multi-stakeholder perspectives to understand the contextual and institutional dynamics of AI-driven innovation and sustainable development. Methods may include interviews, ethnographies, and participatory approaches.
3. Mixed-Methods Approaches: Research combining quantitative and qualitative techniques to capture both the measurable impacts of AI-driven solutions and the deeper sociocultural implications of their implementation.
4. Novel Methodological Contributions: Innovative approaches to integrating AI technologies with traditional research methods in sustainability science, urban planning, and public-private-university collaborations.
We invite researchers and practitioners from various disciplines to submit their work, offering methodological, research, and practical contributions that address the contemporary challenges of sustainable development.
List of Topic Areas
The Special Issue will cover a broad range of themes related to sustainable development, including but not limited to:
• AI Applications for Sustainable Development of Business Models
• Public-Private-University National and International Partnerships for AI-driven Innovation
• Urban Planning and Sustainable Transport
• AI-driven Social Innovation for Sustainable Communities
• Financing Sustainable Development AI-Projects
• AI and Public Policy Implementation for Sustainability
• AI, Environmental Management, and Smart Cities
• AI-based methods and algorithms for solving classification, prediction, and clustering tasks in urban areas and networks.
Submission Information
Papers should be submitted via the journal’s online submission system available through the journal homepage here.
When submitting, please choose the special issue: “AI-Driven Innovation and Multi-Sector Collaborations for Sustainable and Urban Development,” as the article type from the drop-down menu.
All papers must follow the guidelines outlined by the journal for submissions.
Submitted articles must not have been previously published, nor should they be considered for publication elsewhere while under review for this journal.
For any questions, interested authors can contact the guest editors.
This journal offers the option to publish Open Access. You are allowed to publish open access through Open Choice. Please explore the OA options available through your institution by referring to our list of OA Transformative Agreements.
Publishing Model: Hybrid
Deadline: Dec 31, 2025
Please sign in or register for FREE
If you are a registered user on Research Communities by Springer Nature, please sign in