Tag Archives: unruly_complexity

Three angles from which to view the practice of researchers

My book, Unruly Complexity: Ecology, Interpretation, Engagement (Taylor 2005), considers three angles—like facets of a crystal—from which to view the practice of researchers:

A.  their study of complex situations;

B.  their interactions with other social agents to establish what counts as knowledge; and

C.  their efforts to pursue social change in which they address self-consciously the complexities of their own situatedness as well as of the complexities of the situation studied.

These angles are evident in the larger structure of the book’s three parts: I. Modeling ecological complexity, II. Interpreting ecological modelers in their complex social context; and III. Engaging reflexively within ecological and social complexity.  The complex situations referred to in angle A are primarily those studied in ecology and socio-environmental research, but the complexity of influences studied in the interpretation of science leads to an equivalent set of three angles.

For each angle, I discuss problems with simple formulations of well-bounded systems that have coherent internal dynamics and simply mediated relations with their external context (labeled type 1 formulations in Chapter 6).  I contrast these formulations with work based on dynamics among particular, unequal units or agents whose actions implicate or span a range of social domains (type 3).  I note, however, that simple formulations are easier to communicate than reconstructions of particular situations and simple formulations appear to have more effect on social mobilization.  I introduce, therefore, an in-between kind of formulation (type 2): simple themes that open up issues, pointing to greater complexity and to further work needed in particular cases.  Indeed, opening out across boundaries and opening up questions provides the impetus from each chapter to the next.  This mode of expository and conceptual development is conveyed by the summary in the next post of the book’s themes and the questions opened up.

This 3×3 structure (summarized in a subsequent post) should be applicable to other fields with complex subject matters.

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Taxonomy of heterogeneities

Contention motivating this taxonomizing: Research as well as the application of knowledge resulting from research are untroubled by heterogeneity to the extent that populations are well controlled. Such control can only be established and maintained with considerable effort or social infrastructure, which invites attention to possibilities for participation instead of control of human subjects.

The taxonomizing is an incomplete work in progress; comments welcome.

Kinds of heterogeneity

Static 1. There is an assortment, each a separate type (“cabinet of curiosities”)
or 2. Mixture of types (e.g., allelic heterogeneity & locus heterogeneity in genetics)
Variational 3. Trait = composite of types (analogy: the 3 components of a triathalon)
4. There is variation, not types
5. Variation in a set of traits involves a composite of variance/covariance structures (statistical heterogeneity)
6. When similar responses of different individual (e.g., genetic) types are observed, it is not necessarily the case that similar conjunctions of risk or protective factors have been involved in producing those responses (=possibility of “underlying heterogeneity”)
Dynamic 7. Variation produces qualitative changes in results from standard theory based on uniform units (e.g., theory about Malthusian population growth, tragedy of the commons, prisoner’s dilemma)
8. “Unruly complexity,” which arises whenever there is ongoing change in the structure of situations that have built up over time from heterogeneous components and are embedded or situated within wider dynamics. (Synonym: “intersecting processes”)
8a. In heterogeneous construction researchers establish knowledge and technological reliability through practices that are developed through diverse and often modest practical choices. This is the same as saying they are involved in contingent and on-going mobilizing of diverse materials, tools, people, and other resources into webs of interconnected resources.
Dynamic-participatory 9. Multiple points of engagement allow for participatory restructuring of unruly complexity or heterogeneous construction
10. Participatory restructuring, which occurs in tension with deployment or withholding of trans-local knowledge and resources.

Actions corresponding to each kind of heterogeneity

including the control (C) that allows one not to be troubled by the heterogeneity and possibilities for participation (P)

1. Question [P] (or suppress the question [C]) about why this assortment has been collected into one list.
2. In medical sociology Brown & Harris find common meaning despite different types of experience (through coding of sameness despite surface heterogeneity).
3. Disaggregate/decompose into separate phenomena
4. C: Make people fit types (stereotyping, panopticon, screening & surveillance, public health measures, diagnostic manuals, reassignment surgery…) Control/ignore non-conformers.
5.
6. C: Look for subclasses in which underlying factors are uniform. If found, use to probe or extrapolate (perhaps unsuccessfully) back to other subclasses.
7.
8. Diagramming of intersecting processes, which exposes multiple points of engagement->8a
8a. Mapping by researchers of situations and situatedness [P]
9. Well-facilitated participatory processes
10.

References

Taylor, P. J. (2005). Unruly Complexity: Ecology, Interpretation, Engagement. Chicago, University of Chicago Press.
Taylor, P. J. (2009). “Infrastructure and Scaffolding: Interpretation and Change of Research Involving Human Genetic Information.” Science as Culture, 18(4):435-459.
Taylor, P. J. (2010). “Three puzzles and eight gaps: What heritability studies and critical commentaries have not paid enough attention to.” Biology & Philosophy, 25:1-31. (DOI 10.1007/s10539-009-9174-x).

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2. Taylor 2009
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10. Taylor 2009

Theorizing about Ecological Complexity, mid 1980s-2000

Constructionist and landscape views (Taylor 2005, Chapter 1, Part A) reinforce other currents that have undermined the aspirations of earlier decades for identifying general principles about systems and communities (Kingsland 1995, 213-251; Taylor and Haila 2001).  Since the 1980s ecologists in general have become increasingly aware that situations may vary according to historical trajectories that have led to them; that particularities of place and connections among places matter; that time and place is a matter of scales that differ among co-occurring species; that variation among individuals can qualitatively alter the ecological process; that this variation is a result of ongoing differentiation occurring within populations—which are specifically located and inter-connected—and that interactions among the species under study can be artifacts of the indirect effects of other “hidden” species (see Taylor 2005, Chapter1, section B).

In patch dynamic studies, for example, the scale and frequency of disturbances that create open “patches” is now emphasized as much as species interactions in the periods between disturbances (Pickett and White 1985).  Studies of succession and of the immigration and extinction dynamics for habitat patches pay attention to the particulars of species dispersal and the habitat being colonized, and how these determine successful colonization for different species (Gray et al. 1987).  Meta-population theory examines the persistence not of communities but of populations (or phoretic associations of communities on carrier species) in a landscape of patches (Hastings and Harrison 1994).  On a larger scale such a shift in focus is supported by biogeographic comparisons which show that continental floras and faunas are not necessarily in equilibrium with the extant environmental conditions (Haila and Järvinen 1990).  From a different angle, models that distinguish among individual organisms (in their characteristics and spatial location) have been shown to generate certain observed ecological patterns, such as patterns of change in size distribution of individuals in a population over time, where large scale, aggregated models have not (DeAngelis and Gross 1992).  And, the effects mediated through the populations not immediately in focus or unrecognized upset the methodology of observing the direct interactions among populations and confound many principles, such as the competitive exclusion principle, derived on that basis (Taylor 2005,Chapter 1, section B; Wootton 1994).

By and large philosophers of ecology, environmental ethicists, environmentalists, and others who invoke principles of ecology have yet to address the implications for their fields of this picture of ecological complexity (Taylor 1997a; Taylor and Haila 2001).

Extracted from Taylor, P.J. (2005) Unruly Complexity: Ecology, Interpretation, Engagement (U. Chicago Press).

References

DeAngelis, D. L. and L. J. Gross (Eds.) (1992). Populations and Communities: An Individual-based Perspective. New York: Chapman and Hall.

Gray, A. J., M. J. Crawley and P. J. Edwards (Eds.) (1987). Colonization, Succession and Stability. 26th Symposium of the British Ecological Society. Oxford: Blackwell.

Haila, Y. and O. Järvinen (1990). “Northern conifer forests and their bird species assemblages,” in A. Keast (Ed.), Biogeography and Ecology of Forest Bird Communities.  The Hague: SPB Acad. Publishing, 65-81.

Hastings, A. and Harrison, S.: 1994, ‘Metapopulation dynamics and genetics’,  Annual Review of Ecology and Systematics 25, 167-188.

Kingsland, S. (1995). Modeling Nature:  Episodes in the History of Population Ecology. Chicago: University of Chicago Press. 2nd. ed., 213-251;

Pickett, S. T. A. and P. S. White (Eds.) (1985). The Ecology of Natural Disturbance and Patch Dynamics. Orlando, FL: Academic Press.

Taylor, P. J. and Y. Haila (2001). “Situatedness and Problematic Boundaries: Conceptualizing Life’s Complex Ecological Context.” Biology & Philosophy 16(4): 521-532

Wootton, J. T. (1994). “The nature and consequences of indirect effects in ecological communities.” Annual Review of Ecology and Systematics 25: 443-466.

What if I think that everything is already unruly complexity? II

What if everything is already unruly complexity?

1st Answer (after defining and illustrating the concept): There’s a qualitative difference in analysis of causes & implications
This leads to Question 2: … implications for whom?

Answer to Q2: Researcher in dialogue between models & phenomena
but this is embedded in dialogue with diverse social agents to establish significant knowledge & subject to ongoing restructuring.

This leads to Question 3: What is the role of the researcher in this dual dialogue?

(Notice that, as in the two islands scenario, we have a sequence of 1. simple well-bounded system (researchers in dialogue [using evidence & models] with real world); 2. simple themes, opening things up (researchers are also social beings, so there must be a dialogue with funders, audience, technicians, etc.—indeed, researchers must always already be aware of this); 3. differentiated, locally particular accounts (how the dual dialogue plays out in particular instances—and how researchers could more self-consciously address the dual dialogues).

What if everything is already unruly complexity? Putting together the ideas above and in the previous post implies that anyone thinking that faces
“the challenge…
of using their knowledge, themes, and other awareness of
complex situations and situatedness
to contribute to a culture of participatory restructuring
of the distributed conditions of knowledge-making and social change.”[*]

That challenge cannot be addressed alone,  nor primarily through our accounts of the world.

* Page 203 in Taylor, P.J. (2005) Unruly Complexity: Ecology, Interpretation, Engagement (U. Chicago Press).  The book as a whole elaborates the sequence of thinking in these two posts.

What if I think that everything is already unruly complexity?

What if I think that everything is already unruly complexity? What do I do?

First, I need to define for whoever is reading what I mean by that term. Unruly complexity refers to situations that
1. consist of heterogeneous components
2. are built up over time and subject to ongoing restructuring
3. are embedded in wider dynamics
Equivalently, for such situations:
1. definite boundaries are lacking
2. what goes on “outside” continually restructures what is “inside”
3. diverse processes come together to produce change

Definitions are best accompanied by an illustration. This is provided the case of soil erosion in a mountainous agricultural region in Oaxaca, Mexico.

Back to the question. What if everything is already unruly complexity?
My first Answer is there’s a Qualitative difference in analysis of causes and in implications drawn from such an analysis.
This answer is well illustrated by the two islands scenario regarding population growth.

The two islands scenario also illustrates an expository or conceptual theme, namely, the use of simple themes or scenarios that are readily digested but undermine simple, system-like formulations (such as population growth leads to environmental degradation). Instead, these themes or scenarios open up issues, pointing to greater complexity and to further work needed in particular cases (such as the case of soil erosion in a mountainous agricultural region in Oaxaca, Mexico). These “opening-up themes” call for or invite work based on dynamics that develop over time among particular, unequal agents whose actions implicate or span a range of social domains.

Back to the question: What if everything is already unruly complexity? and the first Answer that there’s a Qualitative difference in analysis of causes and in implications drawn from such an analysis. This leads to a new Question: Qualitative difference in analysis of causes and implications… for whom? See next post.

The challenge of integrating ecological dynamics into evolutionary theory VI: Five approaches

Integrating the structure and dynamics of evolution’s ecological context (see previous posts) remains a neglected project within evolutionary theory.  Nevertheless, the different approaches to theorizing ecological organization can still be read in terms of the ways that evolutionary theory fits into them, whether or not this is made explicit.  Table 1 provides a classification of five basic orientations.

Central to the first three orientations is the notion of system, which I use in the strong sense of an entity that has clearly defined boundaries and has coherent internal dynamics, dynamics that govern the system’s responses to external influences and determine its structure, stability and development over time (Taylor 1992). System in this sense can refer not only to the basic units of systems ecology, but also to the guilds and communities of community ecology.  These three orientations differ according to the relative time scales of ecological and evolutionary processes.  In contrast to viewing ecological organization as system-like, various ecologists have emphasized what I call its “unruly complexity” (Taylor 2005).  That is, organisms and processes transgress the boundaries of any unit of ecological structure, spanning levels and scales; natural categories for and reduction of the complexity are elusive; ecological structures are subject to restructuring; control and generalization are difficult.  The two non-system orientations differ according to whether this unruly complexity can be disciplined theoretically.   Table 1’s distinctions are illustrated in Taylor (2000) through a review of twentieth century theories of ecological organization.

In the next post in the series, I note Darwin’s keen awareness of the structure and dynamics of evolution’s ecological context and mention some research that follows in that tradition.

Table 1. Five orientations to theorizing ecological organization and evolution.

Focus Orientation Time scales
system (or community) system evolves as a Coherent whole Fast return to equilibrium; slow change or evolution of system
individuals in context of system Stable system Fast return to equilibrium

intermediate speed evolution of population of individuals

slow change of system

system transient, yet Regularly reoccurring Fast passing of transient context (e.g.,succession)

intermediate speed evolution of population of individuals

slow change in nature of transient context

ecological organization as not system-like Anti-Theory Relevant processes not separable into “ecological” and “evolutionary” time scales
unruly complexity can be Disciplined

References
Taylor, P. J. “Community” pp. 52-60 in E.F. Keller & E. Lloyd (eds.) Keywords in Evolutionary Biology, Harvard University Press, 1992
—- “From natural selection to natural construction to disciplining unruly complexity: The challenge of integrating ecology into evolutionary theory,” in R. Singh, K. Krimbas, D. Paul & J. Beatty (eds.), Thinking About Evolution: Historical, Philosophical and Political Perspectives, Cambridge: Cambridge University Press, 377-393, 2000.
—- Unruly Complexity: Ecology, Interpretation, Engagement Chicago: University of Chicago Press, 2005.