APUNTES EN TORNO AL RENDIMIENTO ACADÉMICO

understanding

Newell and Proust (2012) developed a three-stage modelling protocol they termed feedback-guided analysis to address the complexity of SESs, and to develop simple structures that have few variables (the most important ones) yet are capable of enabling the study of the behaviour of systems with a high number of variables (Dyball and Newell, 2015). The steps are:

1) Develop an overview template, which is an influence diagram that includes few high-level state variables, each representing a major subsystem, and the feedback loops that involve these variables. Each variable is an aggregate of lower-level state variables that become more specific as the analysis goes further. It is important to note that the feedback structure of the overview template is maintained throughout the analysis as it is projected into lower-level structures that eventually become more and more specific.

2) Develop a problem-space diagram. This is a lower-level influence diagram with aggregate variables that are given more specific names than the template variables, depending on the subject under study. The problem space maintains the same feedback structure as its overview template.

3) Isolate specific system(s) of interest (SSoI). This is a projection of the problem space. It is a causal-loop diagram (i.e., polarities can be assigned to its causal links) that includes at least one specific variable from each subsystem in the problem space, and at least one causal link that matches each link in the problem space. SSoI maintains the feedback structure of both its parents above but can include additional variables and causal links. The state variables of SSoI are not aggregates but single, well-defined state variables whose behaviour over time can be observed and, ideally, quantified. Therefore, this feedback structure can facilitate the development of working system dynamic models and help understand the system’s behaviour implied by high-level dynamic hypotheses.

An overview template can be projected into multiple problem space diagrams, each of which can in turn be projected into multiple specific systems of interest, as shown in Figure 2.5.

Figure 2.5: Hierarchical relationship between the overview template, problem- space and SSoI diagrams (adapted from Dyball and Newell 2015)

Based on the feedback-guided analysis concept, Dyball and Newell (2015) developed an overview template with variables, or subsystems, relevant to cultural adaptation of humans in their environments. This template also partly builds on Boyden’s transition framework, which includes a wide range of state variables relevant to SESs, grouped in

Overview template Problem Space 1 SSoI 1a SSoI 1b SSoI 1c Problem Space 2 SSoI 2a SSoI 2b SSoI 2c Problem Space 3 SSoI 3a SSoI 3b SSoI 3c

subsystems that represent human health needs, ecosystem health needs and the concept of biosensitive society (i.e., a society that is ‘truly in tune with, sensitive to, and respectful of the processes of life that underpin our existence’) (Boyden, 2016:42) (see Figure 2.6).

Figure 2.6: The transition framework (adapted from Boyden, 2011)

This overview template is called Cultural Adaptation Template (CAT) (see Figure 2.7). It represents the effect of cultural worldviews, discourses or paradigms on the behaviour of communities, and the way this behaviour affects the health and wellbeing of both humans and the ecosystems in which they live. Paradigms, described by Kuhn (1970:175) as ‘the entire constellation of beliefs, values, techniques, and so on shared by the members of a given community’, have a powerful influence on what their proponents perceive as ‘normal, rational or prudent’ behaviour. Paradigms are of paramount importance in any system, and ‘from them, from shared social agreements about the nature of reality, come system goals and information flows, feedbacks, stocks, flows and everything else about systems’ (Meadows, 2008:163).Therefore, they can help understand the actions and attitudes of their proponents and the behaviour of systems (Dyball, 2015).

CAT, its variables, processes and feedbacks, and tables describing the different links and feedback loops are presented in Figure 2.7.

Culture e.g. worldview Knowledge Beliefs, priorities Societal arrangements e.g. economic system govt. regulations education Human population e.g. numbers Density groupings Human activities- Collective e.g. fuel use Manufacturing Farming, warfare Human activities- Individuals e.g. lifestyles Livelihood, travel Artefacts e.g. buildings Roads, vehicles Machines Vegetable gardens Physical environment e.g. atmosphere oceans, clay, rocks

Living environment e.g. plants, animals,

microbes

e.g. clean air Healthy diet Exercise conviviality

e.g. soil integrity Biodiversity No pollutants Stable climate Human Society Cultural options Biophysical options Biophysical environment Ecosystem health needs Human health needs

Figure 2.7: The cultural adaptation template (Adapted from Dyball and Newell 2015)

The four high-level state variables of the CAT are:

1) State of human health and wellbeing—all the various indicators of the physical and psychological wellbeing of a community.

2) State of ecosystem—all the biophysical elements of an SES, including humans themselves and the physical artefacts they construct, in addition to natural resources and the different ecosystem services that are present in the landscape. 3) State of community—this includes the institutional arrangements a society might

have, such as all formal and informal institutions and institutional practices, and economic, political, legal and civil societal arrangements.

4) State of cultural paradigms—the dominant worldviews, knowledge, beliefs and assumptions held by the community in question.

Tables 2.3–2.4 describe the state-change processes and the feedback loops of the CAT.

State of Cultural Paradigms State of Community State of Ecosystem State of Human Health and Wellbeing

1 2 3 4 5 6 7 Social Effects Environmental Effects Co-effects Health Effects

Table 2.3: State-change processes of CAT (adapted from Dyball and Newell, 2015)

Link Processes represented by the link

L1 Planning and goal-setting activities, driven by the community’s dominant paradigms, that include the design and implementation of social policies and practices.

L2 Learning activities. Observation and assessment of the state and evolution of the community, and the modification of cultural paradigms to take these observations and assessments into account.

L3 Individual and collective activities, influenced by the state of the community, that directly affect an individual’s physiological, psychological and social functioning. L4 Learning activities. Observation and assessment of the state and evolution of

population health and wellbeing, and the modification of cultural paradigms to take these observations and assessments into account.

L5 Individual and collective activities influenced by the state of the community, that directly affect the structure and functioning of the affected ecosystem.

L6 Learning activities. Observation and assessment of the state and evolution of the relevant ecosystem, and the modification of cultural paradigms to take these observations and assessments into account.

L7 Natural processes whereby environmental conditions directly affect human physiological, psychological and social states.

Table 2.4: Feedback loops of CAT (adapted from Dyball and Newell, 2015)

Loop Links Description

Social effects 1-2 Link worldviews and community outcomes. A loop within society that can lead to cultural evolution as long as L2 is strong. This evolution can be either adaptive or maladaptive.

Health effects 1-3-4 A loop within society that can lead to cultural evolution as long as L4 is strong. This evolution can be either adaptive or maladaptive. Environmental

effects

1-5-6 A cross-sector loop that can lead to cultural evolution as long as L6 is strong. This evolution can be either adaptive or maladaptive. Coeffects 1-5-7-4 A cross-sector loop that can lead to cultural evolution as long as L4

is strong. This evolution can be either adaptive or maladaptive. The dynamical effects generated by this loop correspond to Boyden’s ‘co-benefits’, but the use of the more general term ‘coeffects’ allows for co-costs as well as co-benefits.

Links L2, L4 and L6 are processes that represent learning activities. This learning can be beneficial or not beneficial and will affect the level or ‘extent’ of the state of the relevant paradigm, either reinforcing it, or eventually leading to a paradigm shift over time. As noted by Dyball and Newell (2015:128), ‘paradigm shifts are essential mechanisms of cultural adaptation, which can be tracked over time by measuring the changing state of a community’s cultural paradigms’. The learning processes are in turn dictated by changes in the state of paradigms, as represented in links L1, L3 and L5. Depending on the analysis of each paradigm at the level of SSoI, each link will either be positive or negative, and the corresponding loops will be either reinforcing or balancing.

The four variables of CAT are generic and represent the highest order classes of variables of any SES and its processes. Following the feedback-guided analysis explained above, the next step is to project CAT down into problem-space diagrams leading to SSoIs. We can produce as many SSoIs as required to address the number of issues, and the scale and extent of the research.

At the CAT and problem-space levels, the processes representing the linkages between the four variables are represented by numbered arrows. These two diagrams are descriptive. They are schemas of the four state variables and their links and feedbacks. In addition to numbers, the SSoI diagrams have polarity signs (+ or -), which represent the

positive of negative impact of a variable on the level or extent of the other. SSoIs are analytical tools that help present what communities think about how things are or should be. My role as a researcher analysing the system is to present these beliefs and whether they are working.

Using visual representation of the system, one can reduce the complexities normally associated with SES. There is no doubt that there are many variables that influence any particular system at different spatial and temporal scales. However, these variables will generally fall under one of the four generic categories of the CAT.

The simple yet very powerful way of visually representing systems through CAT constitutes an effective means of communication between stakeholders with various backgrounds and interests. The diagrams help establish a common ground on which all parties can meet and communicate with this shared language that overcomes their different specialties and limitations related to their respective fields; they can collectively analyse the system to seek results that benefit them all. The CAT has been successfully used to describe and analyse many complex SESs. For example, Davila and Dyball (2017) used the framework to study food systems in the Philippines and demonstrated that there are two competing paradigms dominating and influencing the system: food security and food sovereignty. Dyball and Newell (2015) also used CAT to study the effect of the ‘limitless growth’ paradigm on sustainability of life in the Anthropocene. Both examples show the value of employing a systemic approach (CAT in this case) towards complex problems facing humans and their environment.