Read the seven against each other.
Each contribution reads the same term and notices different things. That only shows when one thing is held steady and the contributions vary. This page does that.
Pick the contributions, then pick what to hold constant. Start with a person. The same five people live through the same twelve weeks on every page, and each contribution follows a different thread through them. Then try “How it gets hollowed out”. Each contribution has its own way of turning into a slogan.
Relations before things
1 · What exists
What relationships are we not seeing, and which could change the result?
Most analysis is attribute-based. It profiles actors, scores departments and ranks risks one at a time. Relations before things treats the pattern of interaction as primary. Trust, reciprocity, information flow and the tightness of coupling become variables in their own right, not soft context. The lineage runs from Anderson’s “more is different” through Emirbayer’s relational sociology, Fei Xiaotong’s ripples of association and ubuntu’s relational personhood to Bateson’s warm data. Whyte’s relational tipping points show the stakes. Once trust and accountability degrade past a threshold, coordinated action fails however capable the parties are. The contribution is strongest where an intervention works in one place and not another. It is weakest when it turns into the claim that everything is connected.
Dispositions before predictions
2 · How it moves
What is this situation already inclined to do?
Forecasting asks what will happen, and under complexity it does poorly. Dispositional analysis asks something else: what is this system inclined to do, given how it is configured now, and what would change that inclination? Its concepts come from ecology and economics. Attractors are the states a system returns to. Slow variables decide when it tips. Early-warning signals show before a shift, and lock-in makes early choices hard to undo. Jullien’s account of shi, the potential in a configuration, is an older version of the same idea. The contribution moves attention from outcomes to the state of the system. It is weakest when asked for dates.
Plural models before the right model
3 · How we know
What would other credible models say, and what survives across them?
Cilliers showed that complex systems are incompressible. Every model leaves something out, and you cannot know in advance whether what it left out matters. So the search for the right model is the wrong search. This contribution uses several partial models on purpose, built on different simplifications, and trusts the conclusions that survive across them. Levins called that “the intersection of independent lies”. Plurality is treated as a permanent condition, not a stage on the way to agreement. The method is strongest where single-model confidence is the usual cause of failure. It is weakest when the models are not really independent, or when nobody is willing to conclude anything at all.
Where to go next
The seven in full
Each contribution’s page carries the whole term, a picture of it at work outside school, its methods with their evidence ratings, and the reading it comes from.
All seven contributions