Rather, the guiding principles for scientific investigations provide a framework indicating how inferences are, in general, to be supported or refuted by a core of interdependent processes, tools, and practices. Although any single scientific study may not fulfill all the principles—for example, an initial study in a line of inquiry will not have been replicated independently—a strong line of research is likely to do so e. We also view the guiding principles as constituting a code of conduct that includes notions of ethical behavior.
In a sense, guiding principles operate like norms in a community, in this case a community of scientists; they are expectations for how scientific research will be conducted. Ideally, individual scientists internalize these norms, and the community monitors them. According to our analysis these principles of science are common to systematic study in such disciplines as astrophysics, political science, and economics, as well as to more applied fields such as medicine, agriculture, and education.
The principles emphasize objectivity, rigorous thinking, open-mindedness, and honest and thorough reporting. Numerous scholars. For example, inductive, deductive, and abductive modes of scientific inquiry meet these principles in different sequences.
The elements of social scientific thinking
The remainder of this chapter lays out the communal values of the scientific community and the guiding principles of the process that enable well-grounded scientific investigations to flourish. Skilled investigators usually learn to conduct rigorous scientific investigations only after acquiring the values of the scientific community, gaining expertise in several related subfields, and mastering diverse investigative techniques through years of practice.
By habits of mind, we mean things such as a dedication to the primacy of evidence, to minimizing and accounting for biases that might affect the research process, and to disciplined, creative, and open-minded thinking. These habits, together with the watchfulness of the community as a whole, result in a cadre of investigators who can engage differing perspectives and explanations in their work and consider alternative paradigms. Perhaps above all, the communally enforced norms ensure as much as is humanly possible that individual scientists—while not necessarily happy about being proven wrong—are willing to open their work to criticism, assessment, and potential revision.
But scientific knowledge is constructed by the work of individuals, and like any other enterprise, if the people conducting the work are not open and candid, it. Sir Cyril Burt, a distinguished psychologist studying the heritability of intelligence, provides a case in point. Examples of such unethical conduct in such fields as medical research are also well documented see, e.
A different set of ethical issues also arises in the sciences that involve research with animals and humans. The involvement of living beings in the research process inevitably raises difficult ethical questions about a host of potential risks, ranging from confidentiality and privacy concerns to injury and death. Scientists must weigh the relative benefits of what might be learned against the potential risks to human research participants as they strive toward rigorous inquiry.
We consider this issue more fully in Chapters 4 and 6. Throughout this report we argue that science is competent inquiry that produces warranted assertions Dewey, , and ultimately develops theory that is supported by pertinent evidence. Science is a creative enterprise, but it is disciplined by communal norms and accepted practices for appraising conclusions and how they were reached. These principles have evolved over time from lessons learned by generations of scientists and scholars of science who have continually refined their theories and methods.
This principle has two parts. The first part concerns the nature of the questions posed: science proceeds by posing significant questions about the world with potentially multiple answers that lead to hypotheses or conjectures that can be tested and refuted. The second part concerns how these questions are posed: they must be posed in such a way that it is. A crucial but typically undervalued aspect of successful scientific investigation is the quality of the question posed. Moving from hunch to conceptualization and specification of a worthwhile question is essential to scientific research.
Indeed, many scientists owe their renown less to their ability to solve problems than to their capacity to select insightful questions for investigation, a capacity that is both creative and disciplined:. The formulation of a problem is often more essential than its solution, which may be merely a matter of mathematical or experimental skill.
To raise new questions, new possibilities, to regard old questions from a new angle, requires creative imagination and marks real advance in science Einstein and Infeld, , p. Questions are posed in an effort to fill a gap in existing knowledge or to seek new knowledge, to pursue the identification of the cause or causes of some phenomena, to describe phenomena, to solve a practical problem, or to formally test a hypothesis. A good question may reframe an older problem in light of newly available tools or techniques, methodological or theoretical.
For example, political scientist Robert Putnam challenged the accepted wisdom that increased modernity led to decreased civic involvement see Box and his work has been challenged in turn.
A question may also be a retesting of a hypothesis under new conditions or circumstances; indeed, studies that replicate earlier work are key to robust research findings that hold across settings and objects of inquiry see Principle 5. A good question can lead to a strong test of a theory, however explicit or implicit the theory may be. The significance of a question can be established with reference to prior research and relevant theory, as well as to its relationship with important claims pertaining to policy or practice. In this way, scientific knowledge grows as new work is added to—and integrated with—the body of material that has come before it.
This body of knowledge includes theo-. In political scientist Robert Putnam was in Rome studying Italian politics when the government decided to implement a new system of regional governments throughout the country. This situation gave Putnam and his colleagues an opportunity to begin a long-term study of how government institutions develop in diverse social environments and what affects their success or failure as democratic institutions Putnam, Leonardi, and Nanetti, The researchers found converging evidence of striking differences by region that had deep historical roots.
The results also cast doubt on the then-prevalent view that increased modernity leads to decreased civic involvement. The civic ethos of traditional communities must not be idealized. The findings of Putnam and his colleagues about the relative influence of economic development and civic traditions on democratic success are less conclusive, but the weight of the evidence favors the assertion that civic tradition matters more than economic affluence.
This and subsequent work on social capital Putnam, has led to a flurry of investigations and controversy that continues today. Indeed, science is not only an effort to produce representations models of real-world phenomena by going from nature to abstract signs. Embedded in their practice, scientists also engage in the development of objects e. A review of theories and prior research relevant to a particular question can simply establish that it has not been answered before. Once this is established, the review can help shape alternative answers, the design and execution of a study by illuminating if and how the question and related conjectures have already been examined, as well as by identifying what is known about sampling, setting, and other important context.
Stokes , p. Work directed toward applied goals can be highly fundamental in character in that it has an important impact on the conceptual structure or outlook of a field. Moreover, the fact that research is of such a nature that it can be applied does not mean that it is not also basic. We recognize that important scientific discoveries are sometimes made when a competent observer notes a strange or interesting phenomenon for the first time. In these cases, of course, no prior literature exists to shape the investigation.
And new fields and disciplines need to start somewhere. Our emphasis on linking to prior literature in this principle, then, applies generally to relatively established domains and fields. Since science is concerned with making sense of the world, its work is necessarily grounded in observations that can be made about it.
Thus, research questions. Answers to these questions lie in realms other than science. Scientific theories are, in essence, conceptual models that explain some phenomenon. Indeed, much of science is fundamentally concerned with developing and testing theories, hypotheses, models, conjectures, or conceptual frameworks that can explain aspects of the physical and social world. Examples of well-known scientific theories include evolution, quantum theory, and the theory of relativity.
To be sure, generalized theoretical understanding is still a goal.
However, some research in the social sciences seeks to achieve deep understanding of particular events or circumstances rather than theoretical understanding that will generalize across situations or events. Between these extremes lies the bulk of social science theory or models, what Merton called.
Philosophers of science have long debated the meaning of the term empirical. As we state here, in one sense the empirical nature of science means that assertions about the world must be warranted by, or at least constrained by, explicit observation of it. However, we recognize that in addition to direct observation, strategies like logical reasoning and mathematical analysis can also provide empirical support for scientific assertions. Subsequently, however, analysis of light energy absorbed by Earth, measured from the content of organic material in geological sediment cores, raised doubts about this correlation as a causal mechanism e.
The modest change in eccentricity did not make nearly enough difference in incident sunlight to produce the required change in thermal absorption. Examples of such mid-range theories or explanatory models can be found in the physical and the social sciences. These theories are representations or abstractions of some aspect of reality that one can only approximate by such models. Molecules, fields, or black holes are classic explanatory models in physics; the genetic code and the contractile filament model of muscle are two in biology.
He based the hypothesis on astronomical observations showing that the regions above and below the ecliptic are laden with cosmic dust, which would cool the planet. Farley had begun his research project in an effort to refute the Muller inclination model, but discovered—to his surprise— that cosmic dust levels did indeed wax and wane in sync with the ice ages. As an immediate cause of the temperature change, Muller proposed that dust from space would influence the cloud cover on Earth and the amount of greenhouse gases—mainly carbon dioxide—in the atmosphere.
Indeed, measurements of oxygen isotopes in trapped air bubbles and other properties from a ,year-long Antarctic ice core by paleoceanographer Nicholas Shackleton provided more confirming evidence. Still, no one knows how orbital variations would send the carbon dioxide into and out of the atmosphere. And there are likely to be other significant geologic factors besides carbon dioxide that control climate.
There is much work still to be done to sort out the complex variables that are probably responsible for the ice ages. Theory enters the research process in two important ways. First, scientific research may be guided by a conceptual framework, model, or theory. Researchers seek to test whether a theory holds up under certain circumstances. Here the link between question and theory is straightforward. For example, Putnam based his work on a theoretical conception of institutional performance that related civic engagement and modernization.
A research question can also devolve from a practical problem Stokes, ; see discussion above. In this case, addressing a complex problem like the relationship between class size and student achievement may require several theories. Indeed, the findings from the Tennessee class size reduction study see Box have led to several efforts to devise theoretical understandings of how class size reduction may lead to better student achievement. Scientists are developing models to understand differences in classroom behavior between large and small classes that may ultimately explain and predict changes in achievement Grissmer and Flannagan, That is, the choice of what to observe and how to observe it is driven by an organizing conception—explicit or tacit— of the problem or topic.
Thus, theory drives the research question, the use of methods, and the interpretation of results. Research methods—the design for collecting data and the measurement and analysis of variables in the design—should be selected in light of a research question, and should address it directly. Methods linked directly to problems permit the development of a logical chain of reasoning based.
The process of posing significant questions or hypotheses may occur, as well, at the end of a study e. For clarity of discussion, we separate out the link between question and method see Principle 3 and the rigorous reasoning from evidence to theory see Principle 4. In the actual practice of research, such a separation cannot be achieved. Debates about method—in many disciplines and fields—have raged for centuries as researchers have battled over the relative merit of the various techniques of their trade.
The simple truth is that the method used to conduct scientific research must fit the question posed, and the investigator must competently implement the method. Particular methods are better suited to address some questions rather than others. The rare choice in the mid s in Tennessee to conduct a randomized field trial, for example, enabled stronger inferences about the effects of class size reduction on student achievement see Box than would have been possible with other methods. This link between question and method must be clearly explicated and justified; a researcher should indicate how a particular method will enable competent investigation of the question of interest.
Moreover, a detailed description of method—measurements, data collection procedures, and data analyses—must be available to permit others to critique or replicate the study see Principle 5. Finally, investigators should identify potential methodological limitations such as insensitivity to potentially important variables, missing data, and potential researcher bias. The choice of method is not always straightforward because, across all disciplines and fields, a wide range of legitimate methods—both quantitative and qualitative—are available to the researcher.
For example when considering questions about the natural universe—from atoms to cells to black holes—profoundly different methods and approaches characterize each sub-field. While investigations in the natural sciences are often dependent on the use of highly sophisticated instrumentation e. For example, in two Danish zoologists identified an entirely new phylum of animals from a species of tiny rotifer-like creatures found living on the mouthparts of lobsters, using only a hand lens and light microscope Wilson, , p. However, the Glass and Smith study was criticized e.
Some subsequent reviews reached conclusions similar to Glass and Smith e. In the midst of controversy, the Tennessee state legislature asked just this question and funded a randomized experiment to find out, an experiment that Harvard statistician Frederick Mosteller , p.
If a research conjecture or hypothesis can withstand scrutiny by multiple methods its credibility is enhanced greatly. As Webb, Campbell, Schwartz, and Sechrest , pp. The experiment began with a cohort of students who entered kindergarten in , and lasted 4 years. After third grade, all students returned to regular size classes. Although students were supposed to stay in their original treatment conditions for four years, not all did.
Three findings from this experiment stand out.
On the basis of our findings, we argue that there are reasons to favor pluralism over unification as a methodological approach to integrated research on social and natural dimensions of sustainability. In the Conclusions section, we conclude with five key messages. The use of the word resilience has a long history replete with diverse meanings ranging from bouncing, leaping, and rebounding, to human resourcefulness, to elasticity and resistance properties in materials including steel, yarn, and woven fabrics 1.
In contemporary debates, it is a commonly held view that resilience is concerned with the ability to cope with stress or, more precisely, to return to some form of normal condition after a period of stress. Early on, ecological theory was associated with the equilibrium and stability of ecosystems. Resilience has longer roots in psychology than in ecology 4. In psychology, some scholars argue that resilience is a personal trait 5 , although it is most commonly understood as a process 6 —a dynamic process of positive adaptation within the context of significant adversity, trauma, tragedy, threats, or significant sources of stress 7.
In the case of chronic adversity, it refers to long-term outcomes, such as children eventually achieving a normal adulthood 8. This meaning has been called emergent resilience 9.
In some circles, this change shifted the focus from individual resilience to include the role of social capital in communities in which individuals are embedded Research on community resilience includes insights on health and human development, and can potentially be seen as an example of co-development with resilience theory in the context of socio-ecological systems SESs 12 — It is clear that resilience thinking describes important attributes of ecosystems, of materials, and of human beings, that is, the ability to cope with, and recover after, disturbance, shocks, and stress.
However, with popularity comes the risk of blurring and diluting the meaning From a scientific point of view, one might think that scientists rooted in resilience research would try to safeguard the concept from inconsistency and ambiguity because conceptual accuracy and precision are of fundamental importance and often considered a prerequisite in science However, we take transformation, which seems to be contrary to what Walker et al. Recently, resilience thinkers address this ambiguity in the meaning of resilience, which seems to include both change and resistance to change, by arguing that it is the critics who misinterpret or misunderstand the notion of transformation However, the tendency to see resilience and all that it entails as desirable is an important reason, we argue, why social science focusing on social change over stability has difficulties accepting the resilience concept.
In addition, resilience aspires to be an integrated framework to be used across the boundaries of the natural and social sciences [ 3 , p.
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Social scientists have therefore argued that the application of resilience to social systems requires more solid theoretical grounding At this point, we acknowledge the long history of the concept of resilience with its many articulations, iterations, and positive attributes. However, it is an elusive concept in need of structuring, so we suggest a typology organized around two conceptual meanings on one axis, and two attributes on the other, describing the four main types of definition frequently used in the scientific literature Table 1. Each of the four distinct types is exemplified by one representative article.
In the following five subsections, we identify core concepts and principles in resilience theory that create theoretical tensions and methodological barriers between the natural and social sciences and thus stand in the way of a constructive dialogue on knowledge integration between disciplines. To evaluate the ontological commensurability of resilience theory with social science, we examine the concepts and principles deployed in resilience research in terms of their assumptions about society and the standing of these assumptions in social science.
In ecology, the concept of resilience is associated with a system ontology and ecosystems as the target domain. Whereas some ecologists study ecosystems for the interactions between predators and their prey, others see ecosystems as flows of energy. In the literature on SESs, the system under study commonly has a prominent ecosystem component such as a coral reef 28 , fisheries 29 , forests 30 , grasslands 31 , or wetlands The notion of system is indispensable to resilience, and having decided on the phenomenon to be explained, the system boundaries need to be defined.
Beyond that, resilience is sometimes used to describe and analyze social entities such as institutions, organizations, cities, or states Even if the system ontology is essential in resilience thinking, there are surprisingly few studies addressing resilience at the system level. In a recent quantitative meta-analysis of published articles on resilience, Downes et al. In the social sciences, system ontology is not new or unknown. To be noted here, some early social system theories emanated from physics and biology. In sociology, Talcott Parsons, another proponent of system theory, was inspired by Pareto and the emerging system science in biology Intentionally or unintentionally, the current discourse on SESs borrows many of its ideas about society from this early view of social systems inspired by the natural sciences, which is now highly controversial in contemporary social sciences According to Luhmann, a social system consists of nothing but communication; neither material conditions nor human beings are part of it For example, the economic system as we know it is based on money, and money is created by the economic system.
Without an economic system that defines the value of money, it would simply be pieces of paper, and without money, there would be no economic system. This is very different from how we understand ecosystems. Another characteristic of an autopoietic system is that its boundaries are determined by the system itself. In the economic system, anything that is scarce and in demand has a price and is internal to the system, whereas goods and services that are either ubiquitous or not in demand have no price and are external to the system. Hence, an autopoietic system has no direct links to its environment; it is closed.
However, under pressure from its environment, the system may change by shrinking or extending its boundaries. As a whole, the critique points at the problem of using functional systems thinking to describe and explain relations between entities and systems This takes us to the next point: the problem of defining system boundaries. Before that, we should briefly mention World System Theory WST as yet another well-known system theory in the social sciences, with the sociologist Immanuel Wallerstein as its most prominent theorist. It developed in the s out of Marxist thought and builds on dependency theory emerging in the late s as a critique of functionalist modernization theory in development WST is an important source of inspiration to many environmental social scientists 43 —and development thinkers alike—but it is hardly compatible with resilience theory.
Not even planet Earth is an example of a system with clear boundaries owing to its layered atmosphere. In some cases, it is easier to define the system because it may have clear boundaries, or the research focus may allow boundaries to be clearly stipulated. In psychology, the system ontology is well established, and the most fundamental systems under study are fairly well defined such as the individual, the family, the local community, the school, and so forth.
In many instances, it is more difficult to settle the boundaries—in both the natural and the social sciences. A forest, for instance, may have no boundaries that can be unambiguously determined. It may be more or less well connected with other forests, lakes, and rivers in such a way that any suggested boundary will be arbitrary or artificial.
At first blush, a lake ecosystem is clearly separate from the surrounding terrestrial environment. However, some plants along the shoreline may be either partially submerged or rooted in the surrounding land; amphibians move between the shoreline and the water; surrounding trees drop leaves into the water, etc.
The delineation of a system is not just a matter of social or spatial location, and depending on the choice of theory, boundaries will vary. Generally, we seem to understand a system as an entity of a given phenomenon that we want to describe, explain, or interact with—and this has consequences for how we understand the system. Herbert Simon 47 argued that the strength of connections between variables can be used to decompose systems into distinct subsystems. Moreover, it is often claimed 48 that a system is a set of elements standing in reciprocal interrelation.
However, even such systems depend to some extent on pragmatic considerations As an illustration, Collier and Cumming [ 50 , p. In case study design, researchers set boundaries on the basis of research questions, propositions generated from theory, meta-theoretical assumptions, etc. With regard to boundaries, there is no sharp line of demarcation in reality to explain perceived differences between natural or social systems.
Neither in nature nor in society are boundaries fixed unless we first decide on the phenomenon to be described or explained. Pragmatic considerations imply some degree of construction—in both social and natural contexts. There is thus a certain degree of reflexivity among researchers who recognize that system boundaries are constructed, and that sometimes, for various reasons, resilience is contested. In theory and practice, systems and system boundaries are essential components of resilience, although there are many obstacles to systems thinking inherent in contemporary social science.
In particular, system boundaries depend on the assumption that there is a given set of entities and that these are universally recognized across disciplines. However, in the natural sciences, a given set of entities is more accepted than in the social sciences. It is tempting to downplay the conceptual requirements of systems to make resilience applicable to social phenomena, but that would be a clear example of blurring the concept of resilience, which should be avoided because it would result in a less scientific concept. Whereas system is almost a universal concept in the natural sciences, institutions are axiomatic, although interpreted variously, to social science and core to understanding social continuity and change 52 , The use of an institutional lens on the integration of social and natural dimensions could become a methodological linchpin to connect the social and the natural sciences for the sake of sustainability.
This would require not only the use of rational choice institutionalism, as represented by Ostrom 54 and often associated with SESs 55 , but also the involvement of historical, sociological, and discursive institutionalism, which stress the material as well as ideational aspects of society and nature and their dynamics Different institutional theories would treat the idea of system and system boundaries differently.
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This dynamic is often visualized by a ball on an undulating surface with multiple concave shapes. If pushed too hard, or if the walls are lowered, the ball may move into another concave shape, illustrating that the system has exceeded some critical threshold s and shifted into a new equilibrium. An example could be a lake shifting from a vegetation-dominated clear state into a turbid plankton-dominated state The interesting question is whether the lake has shifted into a new system, thus a system transformation, or whether the system is basically the same but with an altered function.
The analogy of the ball and the undulating surface is problematic in relation to social phenomena because of competing explanations and paradigms in the social sciences. In cybernetics, there are two types of feedback mechanisms: negative feedback, which stabilizes the system homeostasis , and positive feedback, which causes exponential change. Applied to social phenomena, this notion of negative and positive feedback is overly simple. Social entities interact back and forth in norm-based processes of continuously interpreted and reinterpreted communication and interaction that may or may not affect behavior—thus indicating less predictability and greater complexity than simple positive or negative feedback 27 , The structural complexity of ecological and social systems can partly be conceived of in similar terms, but the feedback processes associated with each are incomparable because feedback mechanisms in social systems are primarily determined by agency, or structured agency, rather than by structural forces This is especially so because norms influencing agency are dynamic constructs subject to continuous change rather than to static structures The principle of self-organization is a further cornerstone of the resilience discourse In ecology, self-organizing systems are common and perceived as unproblematic because there is often an overarching driver, the attractor, providing the logic of self-organization.
To exemplify this, all leaves in a deciduous boreal forest orient themselves toward the sun to optimize the amount of sunlight that they can capture, thus maximizing the uptake of solar energy, which is an attractor of that system. Even if Smith did not use the term self-organization, what he depicts is almost a perfect illustration of such a system.
Much later, in an argument in favor of market forces and against radical state-oriented reformists, the economist Friedrich Hayek 62 developed the idea of self-organization even further. However, such views of society are contested by scholars outside the neoclassical paradigm. When Polanyi 63 speaks of the emergence of a self-regulating market, he stresses that it relies on strong state interventions, primarily the commodification of land, labor, and money What appears to be self-regulating by some is thus considered the result of political forces and institutional change by others.
An Introduction to Science
As a further illustration, social science offers a vast literature on power as a fundamental and omnipresent force shaping and reshaping interactions, relations, and social not self- organizations, implying various degrees and types of continuity or change In addition, the literature on agency, conflict, institutionalism, structuralism, and other middle-range theories is rich, varied, and frequently used.
Self-organization is aligned with rational choice theory as seen in the works of Elinor Ostrom 54 , 55 , 65 , who was a strong supporter of and contributor to resilience thinking. However, rational choice is often criticized for leaning heavily on the two principles of methodological individualism: of seeing macro patterns as resulting from the aggregation of decentralized choices and of seeing economic change as determined by factor costs land, labor, capital.
Resilience theory is rooted in complexity theory, wherein self-organization is seen as the overriding organizing principle 58 , A conspicuous example is given by Walker et al. When self-organization is used in the social sciences, it is mainly understood as a reaction to power asymmetries and structural inequality such as in the formation of social movements 69 — The understanding of function is a major source of divergence between the natural sciences and contemporary social sciences, but this was not always the case.
In ecological sciences, function is a central theme often defined as the ecological mechanism that maintains the structure and services produced by ecosystems, such as primary production, decomposition, and trophic food chain interactions The early functionalists in the social sciences, such as the sociologist Durkheim and the anthropologist Radcliffe-Brown, argued that the concept of function, when applied to society, can be seen as an analogy between social life and organic life A meaning similar to that used by the early functionalists is found in resilience theory where ecosystems have four main functions exploitation, conservation, release, and reorganization , which according to certain dynamics are responsible for the succession and transformation of ecosystems from one state to another In the seminal book Panarchy [ 74 , p.
As a further description and explanation of the AGIL model, modern societies have acted on all four components according to Parsons: for adaptation, societies developed industries and markets as well as science and technology; for goal attainment, societies developed political institutions; for integration, societies developed civil society and religion; and for latency, societies developed families and schools.
Parson was later criticized for overemphasizing consensus, conformity, stability, and reification. To address this critique, neofunctionalists incorporated more agency, dynamics, and conflict into this thinking There are further concerns with functional definitions of institutions. First, the emphasis on the functionality of institutions implies a conservative approach to social change Second, the existence of malfunctioning institutions is difficult to explain if their role is to perform the very function that defines them Third, the equilibrium tendencies in structural functionalism may not be helpful in a social science analysis 1.
As a reaction to the incapacity of functionalism, such as the inability to explain rapid social change, various conflict theories rooted in the ideas of Karl Marx, Max Weber, and George Simmel emerged in the s and asked other questions about society According to conflict theory, institutions are shaped by existing conflicts, power im balances, and social stratifications in society, which in itself is seen as highly dynamic rather than static as in functionalism On the basis of a wealth of empirical data, the further development of sociological conflict theories has since then emphasized the importance of detailed study of processes in society, thus moving away from the production of grand theory and what was perceived as ideologically based conflict theory Notably, and as a peculiarity, functionalism builds on a nondynamic consensus perspective of society, which echoes the state of a steady equilibrium that resilience theory reacted against and rejected in its own analysis of ecosystems The most fundamental obstacle here, we argue, is the difference in how resilience theory and the social sciences understand society—in terms of social systems, social relations, and social change.
In essence, resilience theory is implicitly based on an understanding of society that resembles consensus theories in sociology, according to which shared norms and values are the foundation of a stable harmonious society in which social change is slow and orderly—and where, in analog, resilience thus becomes the equivalent of stability and harmony or the good norm. However, while previously seen as dominant in sociological theory—though strongly contested, for example, by the critical theory of the Frankfurt School—consensus theories have declined dramatically since the s 41 , giving more space to conflict theory and issues of diversity, inequality, and power.
Conflict theories emphasize conflicting interests between groups in society, meaning that social order is maintained by material or discursive manipulation and control by dominant and powerful groups, and that transformational change can develop from the tensions between these groups and the redistribution of power. In functional approaches, the conservatism is clear: change is understood as coming about due to continuous progressive processes such as the division of labor or differentiation; conflict arises in reaction to these, and a stable society must contain the unrest.
This must be taken into consideration in any serious attempt to bridge the social with the natural sciences, be it via resilience theory and thinking or via other less unifying and thus more methodologically and theoretically pluralist approaches. Whereas most disciplines seek to avoid teleological explanations, biology, and evolutionary biology in particular, is rife with functional claims The striking similarities between resilience theory and rightly abandoned theories of functionalism and structural functionalism in the social sciences, as also noted by others 1 , 79 , are one reason why the resilience discourse does not fit the social sciences.
Resilience theory rests on functionalism as a theoretically superseded understanding of society; furthermore, owing to its emphasis on self-organization, it appears to be aligned with the contemporary neoliberal economics paradigm 86 , This entails a proliferation of market-based instruments for ecosystem management 88 as epitomized by The Economics of Ecosystems and Biodiversity initiative TEEB aiming to help decision-makers recognize, demonstrate, and capture the values of ecosystem services and biodiversity 89 [see also Brown 90 ].
To summarize the argument so far, we conclude that despite its compelling attractiveness in terms of its original coherence, simplicity, and apparent completeness, there are problems in using resilience as a universal concept. Admittedly, it has analytical potential, especially in the serious effort to promote integrated approaches across scales, sectors, and spaces 25 , but not everyone finds it helpful that resilience thinking seeks to combine adaptation dynamic with resistance static in one framing concept 1.
Moreover, whereas resilience theory aims to prevent transitions—or rather, hinder the collapse of a productive system—social theory commonly used in sustainability studies—from transition theory to political ecology—aims to locate and analyze multilevel or multiscalar resistance against change while seeking to stimulate social transformation This incommensurability is problematic for at least two reasons. First, sustainability research needs to consider both continuity and change while also distinguishing between them Second, transformation for the sake of persistence of the system—rather than transformation for profound change—appears counterintuitive to social science thinking.
Whereas studies building on rational choice, as found in the literature on SESs, have difficulties in identifying and explaining change, studies drawing on, for instance, transition theory and discursive institutional theory seek specifically to identify initial change by studying agency, or the thinking and speaking that precedes agency Agency, in turn, can be interpreted differently depending on the use of analytical perspective, be it cultural, discursive, power-based, or a rational choice This text is intended for use in a broad array of the social sciences, including Political Science, Sociology, and Psychology.
Table of contents 1. Thinking Scientifically. The Elements of Science. Measuring Variables and Relationships. Review quote "Well written, easily understood, simple approach to explaining complex concepts to students who have never had the material before. This book shows what the social science enterprise looks like. It also gives students resources and ideas for further exploration. He teaches state and local politics; American politics, parties, campaigns, and elections; comparative electoral systems; and introductory research methods and statistics. His research interests include direct democracy, election systems and representation, political behavior, subnational politics, and the political economy of local development.