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A Complex Thing! Are measures of complexity an end in themselves to address extreme poverty?

7 November 2014

CARE MOZToday’s post is from Emmanuel Asomba, a consultant working on poverty reduction, human development and systematic reviews of development polices and programs.

The most prominent goal of development has been to eradicate extreme poverty. Both literally and figuratively this goal has been part of a prescriptive stroll over the past two decades, moving in a linear fashion. However, along the way, it has become clear that poverty is a multidimensional phenomenon changing across context, thus requiring multiple correspondence analysis and interventions. This is far more amenable to adaptive solutions in social change. It underlies a different vision to address, among others, the interactions between inequality and poverty, primarily to share approaches in different domains, and ultimately to enhance the interconnectedness between institutions to balance social outcomes.

With a number of components, such as behaviors and organizational parameters, needed for development to work, it is important to capture the variability of desired outcomes to adapt social and economic interventions. Proclaiming that social protection programs and job promotion have to “accommodate specificities” is not enough. The transition is to consider how aggregation happens, widening the scope of change by reviewing the relationships between cause and effect to discern how emergent practices can blend to improve rights-based/social justice platforms. This view stresses how change can unfold across converging organizational contexts.

To alter the balance more effectively, interconnections among intervention designs can boost the possibility of generating multidimensional development systems. The idea is to bring about empowerment and cooperation across several sectors and stakeholders, all of them identifying and differentiating the causes of change to come up with more than mere technical fixes. For instance, the ultimate objective of the MDGs (Millennium Development Goals) has been to promote sustainable development across the board. The broad effort of the development community consistent with the post-2015 agenda is to avoid fragmentation. This can be most apparent if human development, food security, access to education, health care, etc, can scale up, increasing relationships, operationalization, transparency and compliance across life-cycle development approaches. These elements are states of matter stemming from observations and applications of qualitative differences in social systems.

Extreme poverty and inequality are complex issues; we have good reasons to think that integrating a mix of alternatives in programming is a constructive route to support the expansion of “ecosystems” or networks of change. This outlook is a way to set the focus on context and variation (see Tony Pike). As a step forward we can test the viability of diverse approaches through the tweaking and sequencing of activities to achieve robust feedback systems.

In the world of complexity as outlined by the DAC Network on Gender Equality, the pragmatic case of Women’s Economic Empowerment (WEE) shows how we can reconcile opinions to combat the isolation caused by extreme poverty, and consequently the deprivation feeding women’s unequal control of assets and income. By emphasizing the improvement of standards of living, especially for low-income women, this concept can approach social-economic programs from a systems-perspective, i.e., adapting and iterating solutions to build local expertise and knowledge to reduce their vulnerability. In tandem with consistent policies, principles of equal rights and equity can help map new conceptions of relationships and interactions between various actors, thus shifting measures of initiatives and ownership in gender relations.

The transition moves away from simplifications, adapting organizational levels and flexibility in interventions. This approach contrasts with conventional approaches to programming by capitalizing among other things on the existence of different feedback loops to recalibrate for instance, women’s bargaining power, or their mobility. So, the idea of cause and effect is brought under new light with pathway models telling the stories of key outcomes and relationships that can generate change or be measured.

An illustration of this complexity paradigm is the way CARE shifted its corporate processes and strategy to grapple with gender equality for its agricultural portfolio targeting high-poverty households in Latin America and Africa. A critical juncture was the need to streamline operational links through gender-sensitive policies as part of the Women Empowerment in Agriculture (WEA) framework. Primarily set to encourage the role of women and girls in leadership by using adaptive paths, the emphasis was on an organization-wide change process to build a collective approach on individual rights. CARE called for the understanding of ecosystems of equal rights to adjust their poverty profiles and policy interventions.

A case in point is the implementation in 2008 of their Income Smoothing through Agricultural Marketing Interventions (ISAMI) in Uganda, involving male decision-makers in supporting women across agricultural networks. Seen through a multidimensional lens, this initiative threw a strong light on the pertinence of joint distribution of disadvantages to address women’s participation in household and community-level decision-making. By engaging local groups to address the nature of the gender division of labor, time poverty, or the gender control of labor and products of labor, this project triggered the emergence of implicit causal pathways that led to robust strategic programmatic shifts.

It evolved around three dimensions and sub-dimensions of women’s empowerment in collective marketing, namely, agency, relations and structure. Out of them came forth, a responsive logic model. It broadened feedback loops on connections and practices (cause-effect chains), thus completing CARE’s multidimensional approach with poverty income measures. The true explanation is that these parameters mapped-out a resilience ecology (Circle of Learning) changing old patterns out of emerging practices (gendered allocation of resources) regulating women’s decision influence in household, market accessibility, or the pursuit and acceptance of accountability.

Global development has to move away from linear restrictions treating complex problems in separation. Fulfilling this objective is likely to create significant advances to meet the challenges of extreme poverty. The extension of multiple perspectives can target inherent complexities, making experimentation and learning mainstream adaptive policy tools.

Useful links

The Social Institutions and Gender Index (SIGI) from the OECD Development Centre is an innovative measure of underlying discrimination against women for over 100 countries. While other indices measure gender inequalities in outcomes such as education and employment, SIGI helps policymakers and researchers understand what drives these outcomes. SIGI captures and quantifies discriminatory social institutions, including early marriage, discriminatory inheritance practices, violence against women, son bias, restrictions on access to public space and restricted access to productive resources.

Applications of complexity science for public policy OECD Global Science Forum

OECD work on gender equality and development

4 Responses leave one →
  1. Ulric Schwela permalink
    November 8, 2014

    If poverty is a complex issue and the article is intended to raise awareness, would it not help to write it in a less complex manner?

  2. lily permalink
    November 18, 2014

    Systems analysis & the tools and techniques for complexity science are certainly most appropriate in aid/development/humanitarian work…including disasters that are man-made/natural/collateral damage from development activities that could be anticipated when appropriate & relevant data are collected, analysed and applied in timely manner – esp by policymakers/development workers/ designers/implementors (national to local levels) and other stakeholders. Considering “data is only as good as it is analyzed and applied”, likewise technology (tools, techniques, systems) is only as good and applied by policymakers in government who have the commitment, political will and leadership for the pursuit of goals on economic growth that is inclusive side by side with good, transparent and accountable governance within a sustainable development framework. The parameters (esp non-parametric including social and cultural factors etc) that will be factored into the analyses are as equally critical. Are there enough resources for timely generation and analyses of data? Who will account for their integrity, efficient and effective use and application vis-à-vis the more convenient political, image-polishing, knee-jerk decisi ons by politicians and their protégés in the bureaucracy?

    • Emmanuel Asomba permalink
      November 19, 2014

      It’s all about the questioning of normative assumptions, however, the extent to which we can find common properties is still debated. Let’s not forget that we have this inclination/bias to lie on a one-dimensional side of thinking or decision, therefore recognizing other dimensions or situations can at times be quite a burden.

  3. Patrick Love permalink*
    November 19, 2014

    Brian Keeley discusses innovative approaches to data collection in this post

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