According to Monchuk (2013), increasing climate shocks have weakened global poverty reduction progress (FAO, 2017). Statistics shows that 87% of natural disasters between 1980 - 2012 were weather-related. Weather related shocks also accounted for 74% of all disaster-related losses in terms of lives and assets within the same period.
In a context where the poor and vulnerable are increasingly facing multidimensional risks, which go beyond socio-economic shocks to shocks resulting from increasing climate changes and natural hazards, there has been an increasing international call - as early as 2007 (UNDP, 2007) - for the mainstreaming of climate change adaptation (CCA) and disaster risk reduction (DRR) strategies in mainstream development practice.
In recent years, different development strategies, one of which is ASP have been spearheading the mainstreaming of CCA and or DRR in development policies, programmes, and projects. Despite the expressed will to mainstream CCA and DRR, there is still many challenges inhibiting effective mainstreaming.
In this article, I try to shed light on some of the factors that negatively affects the integration of DRR and CCA in social protection (SP) systems. But before diving into that, sections 2&3 present a brief description of what ASP is and provides a rationale for mainstreaming CCA and DRR in SP systems.
What is Adaptive Social Protection (ASP)?
Simply put, ASP can be described as a development approach that combines methodological approaches and knowledge from SP, CCA, and DRR so as to comprehensively address the multi-dimensional risks and vulnerabilities suffered by individual and groups by helping them build resilient and adaptable capacities needed to minimise the negative impact of socio-economic, disaster-related and climate-related shocks.
The table below presents types of protection functions that can be offered by an ASP System
Sources: Devereux and Sabates-Wheeler, (2004), Kuriakose et al. (2012), United Nations, 2015b).
The Rationale for ASP Systems
The rational for combining tools and knowledge from the three disciplines arise from the fact that, while SP, CCA and DRR have historically all focused on the reduction of vulnerabilities (Brunori & O’Reilly, 2010) evidence has shown that the understanding, conceptualisation, and approaches applied by each of these disciplines of vulnerability reduction have been limited to targeting specific vulnerabilities of disciplinary interest.
For example, SP mostly focuses on socio-economic vulnerabilities, while CCA mostly focuses on climate-related vulnerabilities. This situation has led to a “piecemeal” approach to vulnerability reduction and further reinforced the prevailing siloed working arrangement between SP, CCA, and DRR agencies (Kuriakose et al., 2012), thereby preventing a more comprehensive strategy.
Considering the siloed context described above, the concept and practice of ASP is being promoted to strengthen the integration of SP, DRR, and CCA so as to ensure a more comprehensive and more mainstreamed strategy towards vulnerability reduction.
Integrating CCA and DRR in SP systems
This section describes the factors that determine the mainstreaming CCA and DRR in SP policies, programmes, and projects. While many more factors can explain this fact, this article analyses these factors across four broad categories. These include; institutional, contextual, technical, and practical factors. While these factors are described here separately, it should be noted that most of them are mutually reinforcing factors.
1. Contextual Factors: Environment specificity
Contextual factors here are characterised as factors that are specific to each country, village, town, or city that determines the likelihood of a climate or disaster shock in the region. For example, countries or regions with traditionally heavy monsoon rains (keeping other factors such as poor urban drainage constant) have a higher risk of experiencing flooding than those without.
Davies et al. (2013) study in South East Asian countries found that the context specificity of each country greatly influenced the extent of mainstreaming of CCA or DRR in SP systems. In regions with higher risks of climate and or disaster related risks, the mainstreaming of CCA and or DRR in SP projects was more likely.
2. Practical factors: Operational level factors
Practical factors look into the mainstreaming CCA and DRR in SP systems from an operational point of view. One of the main results from Eyoh (2018) was that the decision to mainstream CCA or DRR strategies in SP systems of some sampled African countries was determined not only by the type of shock experienced but especially by the specific comparative advantage CCA or DRR had over SP in dealing with that type of shock.
While SP, as shown in Table 1 above, provides preventive functions, the study by Eyoh (2018) found that in areas/times of high-climate or disaster risks, SP projects or programmes opted for mainstreaming DRR preventive mechanisms; early-warning systems that are known to be more effective for shock prevention than those proposed by SP or CCA. The main argument here is that the mainstreaming of CCA or DRR or both in SP systems are more likely once CCA or DRR approaches and tools present a comparative advantage.
Other practical factors have to do with the difference in the scope of the disciplinary targets. For example, while SP focuses more on individual and household risks, DRR focuses more on community level risks, and CCA focuses more on national and international level risks (World Bank,2011).
To the World Bank, such difference in scope and focus comes with several challenges when trying to mainstream both CCA and DRR in SP as this influences the tools and approaches designed by each discipline. While this can be seen as a weakness, it could also be considered a strength given the increasing influence climate changes are having on the emergence of both socio-economic shocks and natural hazards and vice versa.
3. Technical factors: Knowledge level
At the technical level, one of the main challenges to effectively mainstream CCA and or DRR in SP systems emerges from the problem of identification and categorisation of climate and disaster risks. By identification, I refer to the ability of a SP system to effectively diagnose during their design phase the presence of climate or disaster risks. Categorisation on the other hand has to do the ability to clearly define, based on factual evidence, whether a shock/risk is climate or disaster induced.
Various studies have found that SP systems often face a challenge in clearly identifying and categorising climate and disaster risk/shock. According to Venton and La Trobe (2008), the failure to clearly identify and categorise a risk as either climate or disaster-induced has led to wrong decisions on whether to mainstream DRR or CCA functions - or both.
Another major technical problem here has to do with policy evaporation, which is in a way related to the problem of identification and categorisation. The main issue being that, while most national SP policy and strategy documents diagnose the existence of climate and or disaster risks, the strategies developed for implementing the policy sometimes fail to address the climate and disaster risks identified in the diagnostic section. Some scholars, such as Gero et al. (2011) or Browne (2014), have argued that policy evaporation is usually related to a lack of technical capacity and adequate resources to deal with the identified climate and disaster risks.
4. Institutional factors: Stakeholders
By institutional factors, I refer to organisational-level challenges between the disciplines. Fundamental organisational particularities existing among the three disciplines (SP, CCA, and DRR) have been accused by some scholars (Kuriakose, 2012) to be at the centre of the siloed work relations, despite their common goal towards vulnerability reduction.
Fundamentally, SP, CCA, and DRR originate from different ontological, epistemological, and methodological traditions. In other words, while SP has its origin in social sciences, CCA and DRR originate more from natural sciences. According to Davies, Naess, and Béné (2012), this absence of unique origin, which could have provided greater harmony among disciplinary approaches, makes integration in SP systems much harder.
Other institutional factors also have to do with differences among the promoters and funders of the different disciplines, which makes cooperation difficult. As the World Bank (2011) argues, there is a potential trade-off that may spring out from cooperation among the disciplines as this might mean losing-out on the core funders of each discipline. At the national level, cooperation among the agencies might be seen as losing out on autonomy and relevance, including resources.
Findings from Davies et al. (2013) show that where mainstreaming occurred, it was always more in favour of DRR. While other factors, such as the comparative advantage DRR offers for preventive functions, can explain this preference, another factor has to do with the legal backing and ownership DRR enjoys at the national level.
Eyoh (2018) found that, more than 80% of ten sub-Saharan African countries assessed on the extend of CCA and DRR mainstreaming in SP had laws on disaster risks management (DRM) and these laws usually promoted the mainstreaming of DRR in all developmental actions, which was not the case for CCA. For this reason, SP systems were more likely to mainstream DRR than CCA.
In addition to the legal backing, DRR is usually highly prioritised in national government planning than CCA, which is usually an internationally driven agenda. The consequence has been a higher ownership of DRR than CCA at the national level, which in turn explains more mainstreaming of DRR in national SP policies, programmes, and projects. Ultimately, a range of contextual, institutional, practical, and technical factors influence the mainstreaming of CCA and DRR strategies in SP systems.
Browne, E. (2014). Social protection, climate change adaptation and disaster risk reduction (Rapid Literature Review), Birmingham, Uk: GSDRC, University of Birmingham. Accessible: http://gsdrc.org/wp-content/uploads/2015/07/SP_CCA_DRR.pdf
Davies, M., Béné, C., Arnall, A., Tanner, T., Newsham, A., & Coirolo, C. (2013). “Promoting Resilient Livelihoods through Adaptive Social Protection: Lessons from 124 programmes in South Asia”, Development Policy Review, 31(1), 27–58. Accessible: https://doi.org/10.1111/j.1467-7679.2013.00600.x
Devereux & Sabates-Wheeler (2004). “Transformative Social Protection”, IDS Working Papers, (232). Accessible: http://www.ids.ac.uk/publication/transformative-social-protection1
Eyoh, Ukume F. (2018). Adaptive Social Protection Systems in Africa: An Assessment of Social Protection Systems in 10 Sub-Saharan African Countries. Accessible: https://doi.org/10.13140/RG.2.2.27906.73921
FAO (2017). Social Protection, Emergency Response, Resilience and Climate Change: A New Interactive Learning Tool, FAO & Red Cross Red Crescent Climate Centre. Accessible: http://www.fao.org/policy-support/resources/resources-details/en/c/1027727/
Kuriakose, A. T., Heltberg, R., Wiseman, W., Costella, C., Cipryk, R., & Cornelius, S. (2012). Climate responsive social protection (No. 67614) (pp. 1–49), The World Bank. Accessible: http://documents.worldbank.org/curated/en/450791468320349756/Climate-responsive-social-protection
UNDP (Ed.). (2007). Fighting Climate Change: Human Solidarity in a Divided World, Houndmills: Palgrave Macmillan. Accessible: http://hdr.undp.org/sites/default/files/hdr_20072008_summary_english.pdf
Venton, P. & La Trobe, S. (2008). Linking Climate Change Adaptation and Disaster Risk Reduction. Accessible: http://www.preventionweb.net/files/3007_CCAandDRRweb.pdf
World Bank (2011). Social Protection and Climate Resilience, World Bank and IDS.