1. Introduction
2. Patterns
3. Patterns, Objectivity and Truth
4. Patterns and Processes
5. Complexity and Randomness
6. Complexity and Postmodernism
7. Complexity and Rationality
8. Complexity and Professionalism

The Pattern Library:

1. A Pattern of Difference
2. A Pattern of Feedback
3. The Hourglass Pattern
4. The Pattern of Contextual Diminution

Practical PAC:

In my previous posts I have to some extent redefined a lot of philosophical foundations of science, and the argumentation was that we have to do this if we take the many contributions of complexity serious. Complexity, as I have pointed out, means that we can no longer assume a Laplacian 'clockwork universe', which is still the (implicit) foundation of many scientists who believe that reductionism and causal determinismis sufficient to explain everything in our life-world. I have used, amongst others, Gödel and Spencer-Brown to demonstrate that science itself made the discoveries to falsify this Laplacian vision of Universal order, so if scientific dogmatists are mad at me for sweeping the foundations of their 'objectivity' away from under their feet, well..., really...,science kinda did it iself!

On a practical side-note...every mechanical clockwork I know uses grease or oil to keep it ticking, so I feel Laplace could have known for himself that even a deterministic Universe needs a bit of je ne sais qois to prevent its grinding to a halt.

In this post I will introduce Bob, a biologist who is interested in complexity thinking, and who wonders how all the stuff from my previous posts can assist him in his research. Now, Bob is one of those rare exemplars who wants to perform good research, instead of research that is good for his career, and he is willing to accept that the premises of complexity thinking is not going to make things easier for himself. But he likes a challenge, so what the heck!

He accepts that we model our life-world with limited knowledge, that we make selections (so there is a 'purpose' why we choose certain perspectives and data, for which we have to give an account), and that we have to understand that the relationship between our models and the target (that what we are making a model of) has to be an isomorphism, and we have to try to demonstrate this.

Oh yes, his research question is the following:

This is a perfectly sound scientific question, and his supervisor is very happy! Bob, being a straight-A student, knows what his training demands of him, and starts collecting the DNA of homosexuals, compares it with the DNA of a heterosexual control group and, lo and behold, there is a statistically significant difference in the DNA. He discovers a marker X that is found more often in homosexuals.

So far, our complexity-informed scientist is following normal scientific procedures. Now he could write an article for a journal and state 'for a fact':

Currently, a lot of scientific journals would be totally okay with this, but our scientist, being a complexity thinker, is not. He remembers reading an article by Volker Grimm cum suis who stated that a singular association is insufficient to make a complete model that can answer his research question. Maybe it is the other way round, and homosexuality causes the genetic change. Maybe there is a spurious relationship between the marker and homosexuality!

As a result, a decides to visit the sociology department and ask his colleagues there if he can make this statement. The sociologists he visits are themselves also complexity thinkers, and therefore they do not mind that Bob has a rather naive conception of homosexuality; their own research has discovered many people who are homosexual for political reasons, or are homosexual during a certain stage in their life and then become heterosexual again... very difficult stuff to reconcile with genes. Then there are bi-sexuals, transsexuals, women caught in the body of men and vice versa...

But then, they don't know much about the biology behind homosexuality, and there is this strange marker X, so everyone is somewhat naive! Together we learn,  and at least it is becoming clear that there is a lot more to say about homosexuality than a simple linear relationship between a genetic marker and certain aspects of our human 'being' (or being human). As a result, everyone decides to work together in order to prevent that naive preconceptions enter the research. This has now clearly become a bio-social research question, and no-one in the team has the expertise to oversee everything. Our collaborating scientists also realise that homosexuality is complex. A collaborative effort is needed to see how social theory can contribute to a more complete picture.

As the team revisits the data, it appears that the marker returns in heterosexuals as well. Previously Bob would have considered this statistically irrellevant, and maybe (if only for himself) have explained this as being 'homosexuals in denial', but because of the contributions of the sociologists he starts to suspect that the original research question may have been a bit too linear. He then remembers reading a blog on science 2.0 about the 'pattern of difference', which explains why there will be a certain 'bandwith' of sexual preferences, and that social influences may 'interfere' with the biology. Maybe the marker 'expresses itself as homosexuality in a social context, given certain circumstances', as he remembers the cryptic descriptions he had read in the blog.

There is another problem. Bob knows that the structural and ecological perspectives are insufficient to make a conclusive model. He also needs an evolutionary explanation why this marker has become genetically engrained in the DNA. This is problematic, because homosexuality, at first glance, seems to be detrimental for reproductive success. So he hypothesises that either the marker is a spontaneous mutation that occurs regularly, or it is evolutionary persistent, in which case it has to be passed on through the (statistically irrelevant) group of heterosexuals who carry the marker. In order to answer this question, he ask a team of antropologists, historians, archaeologists and others (all complexity thinkers) to help him trace the evolutionary origins of the marker, and the various circumstances that the social groups had to deal with throughout human history, or even further down the evolutionary ladder if necessary.

It turns out that the marker is passed on through heterosexual women, who lived in groups and tribes were the men often went to battle. This results in communities with significantly more women than men. As a consequence, female couples could start stable familes and raised children together, if the morals of the community allowed it. The whole community would benefit as more children were raised successfully. Over time, evolution favoured women who were less strict in their heterosexual preferences, and this evolutionary pattern eventually was engrained in the DNA as marker X. As a side effect, it can also return in men, but the research of the team does provide any clues for an evolutionary benefit there.

As the team digs further, they find out that communities that have significantly higher numbers of individuals who carry the marker, tend to be more open to homosexual relationships. This makes sense, as communities who support parenting by female couples will benefit from this arrangement. Marker X, it turns out, does not not 'code for homosexuality', rather it codes for a larger diversification of female sexual attitudes.

With this, Bob realises that he is no longer looking for a 'genetic cause of homosexuality', because he is dealing with a self-reinforcing causal feedback loop, which he remembers to be a robust process. A structural mismatch between male and female members of a community causes a change in family relationships in the community, which causes a change in the genes, which in turn causes a social change to facilitate this arrangement. Even when the times (and morals) change, the marker manages to get reproduced, even though it may not express itself so openly as homosexuality in more oppressive cultures.

Bob realises that the team has developed a hypothesis that better fits the vocabulary of complexity thinking, which is now based on the question how 'homosexuality can form in a society'. The association between the genetic marker and homosexuality was only a small part of the puzzle, and it wasn't even a direct association to begin with. The gene coded a pattern of certain sexual plasticity, which only results in homosexuality under certain environmental and societal conditions.

I want to stress again that this story is completely made up, a hypothesis at most. There is undoubtedly a lot more to say about this subject, and I'm sure that even this story is still way too simple to answer Bob's complexity-informed research question. But then, we are interested in seeing how data and interpretations influence each other, and the story has a number of things that demonstrate the findings of PAC and complexity:

1. A singular perspective is insufficient to make a model of a complex target. A structural, an ecological (or phenomenological) and an evolutionary/historical perspective will have to be developed in order to understand a complex theme.

2. Research on complexity often concerns itself with the question how something is 'formed' or 'organised' (in a contingent setting).

3. Conplexity is the search for robust patterns or processes. The question of causality is often a rather minor one (but not unimportant) when addressing a complex theme. Cause and effect may easily be reversed, and relationship between cause and effect may be spurious. The cause may be present in one scientific domain, while the effect is manifest in another, which makes interdisciplinary research inevitable.

4. It is highly unlikely that research on complex themes can be fully contained within a scientific discipline. Collaborative efforts of various specialisations are likely going to be the norm. In a mono-disciplinary setting, the research question will have to be constrained, or research/theory from other scientific disciplines will have to be included in the research. A closed epistemological system is likely to create highly skewed models of a complex theme.

5. Research can only reduce the interpretations of the collected data. Every contribution of other scientific disciplines reduces the possible narratives of the association between a genetic marker and homosexuality. If Bob would have stuck to his original mono-disciplinary research, his original hypothesis would remain a fragile one. The question arises...how many research groups in Academia actually assemble such teams to address complex themes?

The take-home message of this hypothetical research question is that collaborations are necessary when addressing complex themes, and so the senseless 'school/method-bashing' between various disciplines, or types of knowledge production, is not helping to make things better. I think that this is one of the reasons why a lot of the more revered thinkers on the complex issues of our time do not confine themselves to 'academically strict' forms of reasoning, but incorporate science in a larger narrative that can also include more philosophical or even literary styles. It is matter of balancing scope and formal correctness (and, very important, respecting your audience).

Complexity is going to make research much more difficult. We need more perspectives, and various forms of data from different fields in order to be able to tell a coherent narrative of forms. With the current publication pressure in academic journals, it is questionable if academia will be able to provide the 'grand picture' of a complex problem. I think that we can already see that this role is taken up much more by journalists, travellers, philosophers and other thinkers who are able to synthesise the specialist data and turn it into a coherent story.