Blog Series: Part 3
Towards a Taxonomy of Anticipatory Methods: Integrating Traditional and Innovative Methods for Migration Policy
Posted on 26th of October 2023 by Sara Marcucci, Stefaan Verhulst
This is the third installment of the Big Data for Migration (BD4M) weekly blog series dedicated to exploring cutting-edge anticipatory methods for migration policy. In our previous post, we illustrated the paradigm shift happening that sees the clear differentiation between quantitative forecasting and qualitative foresight is becoming less distinct. In this week's blog post, we delineate a taxonomy of anticipatory methods, categorizing them into three distinct sub-categories: Experience-based, Expertise-based, and Exploration-based methods. Our focus will be on what the practical applications of these methods are, and how both traditional and non-traditional data sources play a pivotal role within each of these categories.
Experience-based Methods: Understanding Lived Experiences for Anticipation
Experience-based methods in the realm of migration policy focus on gaining insights from the lived experiences of individuals and communities involved in migration processes. These methods allow policymakers to tap into the lived experiences, challenges, and aspirations of individuals and communities, fostering a more empathetic and holistic approach to policy development.
Through the lens of people's experiences and viewpoints, it is possible to create and explore a multitude of scenarios. This in-depth exploration provides policy makers with a comprehensive understanding of these potential pathways, which, in turn, inform their decision-making process.
Figure 1: Visualization of the Experience-based methods category from the BD4M Taxonomy of Anticipatory Methods.
Value: In the complex landscape of migration policy, understanding the experiences of those directly affected by migration processes provides vital context for crafting policies that are relevant, effective, and responsive to people’s needs.
Practical Applications: A few examples of expertise-based anticipatory methods include narrative interviews, focus groups discussions, and participatory action research. First, narrative interviews can delve into the personal stories and lived experiences of migrants, potentially revealing their needs and the challenges they encounter. These intimate narratives offer valuable insights that can inform more compassionate and effective migration policies. Similarly, focus group discussions bring diverse voices together in structured yet interactive settings. In the context of migration, they help policymakers explore the collective experiences and concerns of migrants and host communities. Then, participatory action research takes this a step further by engaging the affected communities in the research process itself. In this collaborative approach, migrants and host communities actively participate in problem identification, research, and solution development. This empowers them to take ownership of the issues they face, ultimately leading to more community-driven and effective policies.
Traditional and Non-Traditional Data: When it comes to anticipating migration trends, both traditional and non-traditional data sources can be valuable. In the context of experience-based methods, traditional data can be gathered from citizen assemblies, providing a structured and face-to-face approach to understanding public perceptions and concerns about migration. Conversely, non-traditional data, like social media analytics, offers a real-time window into public sentiment and emerging trends. Monitoring conversations and trending topics related to migration on social media platforms can provide early indicators of evolving migration patterns. This dynamic data source enables policymakers to stay agile and responsive to the ever-changing landscape of migration issues. Often, combining traditional data, like those resulting from citizen assemblies, with non-traditional data sources, like social media analytics, can enhance policymakers' understanding and ability to anticipate and respond to migration trends effectively. However, in this first category of anticipatory methods as well as in the other two, it is important to consider the potential challenges associated with the use of non-traditional data, which include (a) a lack of a specific procedure that outlines the variables of interest before the data is collected, (b) bias, (c) discriminatory surveillance and lack of group privacy, and (d) data colonialism, especially when the data is owned or enabled by private actors.
Expertise-based Methods: Drawing on Specialized Knowledge for Anticipation
Expertise-based methods rely on the insights and judgments of subject matter experts. In the context of migration policy, these methods are about using expert opinions to make well-informed decisions.
Migration policies involve complex international agreements, humanitarian considerations, and diverse populations. Expertise-based methods are vital for anticipatory decision-making, drawing on specialized knowledge and diverse perspectives.
Figure 2: Visualization of the Expertise-based methods category from the BD4M Taxonomy of Anticipatory Methods.
Value: These methods provide a structured way to access expert insights and knowledge, ensuring well-informed and comprehensive migration policy decisions. They aim to foster knowledge exchange amongst and from people that work in the field of migration and that bring in different, often multidisciplinary expert perspectives.
Practical Applications: A few examples of expertise-based anticipatory methods include the Delphi method, expert panel, and expert interviews. The Delphi method aggregates diverse expert opinions, fostering consensus and reliability in anticipatory insights for migration policy. Expert panels bring together a wide range of knowledge and viewpoints, promoting robust discussions and inclusive decision-making. Finally, expert interviews offer deep dives into specialized knowledge, allowing policymakers to gain nuanced insights, particularly useful when dealing with complex issues such as asylum policy or labor migration regulations.
Traditional and Non-Traditional Data: Both traditional and non-traditional data sources can play important roles in expertise-based anticipatory methods for migration policy. Traditional data, including government statistics and historical records, forms the bedrock upon which experts base their assessments and predictions using methods like the Delphi technique and expert panels. These sources provide the essential context of past trends and benchmarks for robust and informed anticipatory insights. On the other hand, non-traditional data, such as sensor spatial data (which is indeed gathered from experts) or data from digital communication channels amongst expert stakeholders can complement these methods by offering real-time and crowd-sourced information that captures early signals of potential migration trends. In expert interviews, for instance, this dynamic data source can ensure that experts remain attuned to evolving public sentiments and emerging concerns regarding migration, enabling a more adaptive and responsive approach to policy making that incorporates both historical context and the current, ever-changing landscape of migration issues.
Exploration-based Methods: Inspiring Innovative Policies through Unconventional Thinking
Exploration-based methods encourage unconventional thinking and innovative strategies. These methods are about thinking outside the box and exploring unconventional scenarios.
Figure 3: Visualization of the Exploration-based methods category from the BD4M Taxonomy of Anticipatory Methods.
Value: Exploration-based methods are relevant as they inspire creative solutions to address both expected and unexpected challenges in migration. These methods empower migration policymakers to think outside the box and explore unconventional scenarios. For instance, when crafting integration strategies for refugees, exploration-based techniques can be employed to envision unconventional pathways that foster economic self-sufficiency and social cohesion. Likewise, in the context of labor migration, these methods can inspire novel policy frameworks that align labor market needs with the aspirations of migrants, thereby promoting sustainable economic growth. Moreover, exploration-based approaches can be valuable when addressing emerging issues like climate-induced displacement, guiding the development of creative, forward-looking strategies that account for environmental factors and humanitarian concerns.
Practical Applications: Concepts like wildcards, futures-creative models, and science fiction narratives inspire imaginative solutions, shaping visionary policies that are proactive and adaptable. First, wildcards aim to explore unforeseen, low-probability high-impact events, enabling policymakers to prepare for sudden disruptions such as natural disasters or political revolutions. Another example of exploration-based methods is futures-creative models, which encourage innovative thinking by pushing participants to envision alternative futures beyond conventional paradigms. In the context of migration, these models inspire inventive approaches to challenges like forced displacement and integration. Science fiction narratives, on the other hand, provide a creative means to explore and communicate future scenarios influenced by factors such as technology, climate change, and geopolitics, allowing policymakers to engage with potential migration futures and stimulate discussions on policy implications and ethical considerations. When applied in combination or individually, these approaches empower policymakers to anticipate and respond creatively to the complexities of migration, ultimately leading to more adaptive, robust, and innovative policies that cater to the evolving needs of our global community.
Traditional and Non-Traditional Data: Traditional data in exploration-based methods can be used in and sourced from a variety of methods, including scenario writing, scenario workshops, and historical migration trends. Scenario writing utilizes historical data and existing knowledge to construct alternative migration scenarios. Scenario workshops, on the other hand, draw on traditional data for discussions and brainstorming. Historical migration trends, rooted in traditional data sources, offer a foundation for understanding past migration dynamics, allowing policymakers to leverage historical patterns and insights for crafting imaginative scenarios and innovative policies. Non-traditional data sources, on the other hand, include satellite imagery, social media sentiment analysis, and mobile application data. Satellite imagery offers real-time, high-resolution information, making it invaluable for exploration-based methods that require monitoring border movements, environmental shifts influencing migration, and assessing infrastructure developments. Social media sentiment analysis provides insights into public perceptions and evolving trends, facilitating the creation of imaginative scenarios and enhancing the creative thinking process of policymakers. Similarly, mobile application data offers real-time insights into the movements and needs of migrants, aiding scenario development for better-informed and responsive policies. When integrated, amongst themselves and with traditional data sources, these empower exploration-based methods, allowing policymakers to anticipate and creatively respond to the multifaceted challenges of migration.
The blog has attempted to show how each category, from experience-based to expertise-based and exploration-based methods, offers unique insights and value. To address the complexities of human migration comprehensively, we encourage the judicious amalgamation of established and innovative techniques, along with traditional and non-traditional data sources. This may empower policymakers to effectively navigate the intricate terrain of migration, forging policies that are both anticipatory and adaptive.
As we move forward in this series, we'll continue to delve deeper into these methods, exploring their real-world applications and the dynamic interplay between traditional and non-traditional data sources. Stay tuned as we uncover innovative approaches to address the complexities of migration!