Greer uses the example of changing views on marriage and family that have made acceptance of gay marriage even possible. The complex narrative of those changing views is provided as evidence that narrative is most important for understanding what happened. (The narrative is definitely worth reading.) However, the narrative, as unquestionably important as it is, in some ways doesn't explain why it is that a particular view of marriage came to dominate over what had been the dominant view. Why did the change occur? That's what a science of cultural change can explain.
Greer notes that in 1995-96, only 27% of the population thought gays should be allowed to get married, while in 2015, 60% agree with that position. That's a huge change in 20 years. But let's be honest -- the 27% in 1995 was a huge percentage compared to what it had been 20 years before, when it was in the single digits. That means there was a huge leap in support in basically a generation. That means that a huge number of people who once opposed gay marriage now favor it. How do we explain that?
Network theory explains it. When you have a network, you have a situation where you can have explosive change, or emergence. There is a tipping point where the idea, etc. spreads rather quickly. It usually occurs at about 10% saturation. Given the slowness of cultural change, such a massive change in only a generation is rapid.
Greer further asks some great questions:
Today countries with fairly similar economic and demographic profiles—such as much of Western Europe and Japan—have very different attitudes and expectations for the roles men, women, and children are supposed to play in family life. Things like the age at which children leave the home or marry can be quantified and coded with ease. It is much harder to quantify or code how much affection husbands are expected to show their wives, or how harshly parents should discipline their children. The answer to this is that one would have to create a set of network models for each of the cultural traits, from economy to culture to family to whatever other spontaneous order would be involved. There are patterns of psychosocial emergence that take place under changing degrees of interactive density within a population or culture (see the work of Clare Graves and those influenced by him). But these patterns both affect the economy and culture (and others) and are in turn affected by them. We would expect people to have different attitudes based on economy, interactive density, various cultural practices, degrees of trust, etc. Each of these can be modeled and layered on each other to create the rich variety we see in the world.
So what does explain these things? And more importantly, how can we verify if any proposed explanation is true? Is it possible to establish a science of family life?
This may not satisfy many people who think that "science" means "precise prediction." But precise prediction is only appropriate for the simple sciences, like physics and (most) chemistry. It is not at all appropriate for the complex sciences, like biology, psychology, and the social sciences, where we can only ever make pattern predictions.
A great example of a pattern prediction is Turchin's prediction that there will be an increase in political violence in the U.S. in 2020. The research he has done strongly suggests there is a 50 year secular cycle of political violence in the U.S. (The exception, 1820, occurred during the Dalton Minimum, which caused temperatures across the globe to plummet, and may have had a dampening effect on people getting together publicly to get riled up together.) While he can predict that there will be an upswing in political violence, and he can recognize some general elements that drive the cycle, what he cannot do is predict what the precise nature of the conflict will be, what parties will be involved, precisely where the violence will erupt, and precisely what will trigger everything. Also, something could happen to increase or decrease the degree of violence. And 2020 is a more-or-less (within a year or two) prediction. So if it peaks a little early or a little late, Turchin would still be right in his prediction.
Turchin's work involves the creation of a kind of macrohistory comparable to macroeconomics. The patterns that emerge in each macro view involve the kinds of cycles one would expect if positive feedback dominates. Underlying this involves microhistory and microeconomics, which involves the actions of individuals and which is dominates by negative feedback. The fact that different kinds of feedback dominate at different levels of analysis suggests to me that we need to have both approaches if we are going to develop a fully scientific, fully complex understanding of history, culture, economics, or any other social phenomenon we wish to understand. No question that narrative is a vital element, but so too are network models, constructal theory, percolation models, emergence, self-organization, and other related mathematical approaches that will allow us to develop more scientific understandings of human psychosociology.