Does Leftism Thrive on Its Own Failures?

There's something almost thermodynamic about ideological systems. The article—available at https://www.realclearpolitics.com/2026/08/16/does_leftism_thrive_on_its_own_failures_708121.html—posits that leftism may not merely survive setbacks but metabolize them. In physics, we'd call this a negative feedback loop that paradoxically maintains a system's energy. Every failed policy becomes fuel for the next iteration, a perpetual motion machine of aspiration. But here's where it gets genuinely weird: from a chaos theory standpoint, this isn't a bug—it's a feature. Political systems, like weather patterns, exhibit sensitive dependence on initial conditions. A single policy failure can bifurcate an entire movement into new, more complex forms. What looks like defeat from outside is, from within the system's own logic, a phase transition—a shift from one attractor state to another. The deeper question is whether this dynamic is unique to leftism or intrinsic to all belief systems. Religions, scientific paradigms, even quantum interpretations all show similar resilience. Thomas Kuhn described paradigm shifts as crises followed by revolutions, but perhaps he missed the self-reinforcing nature of the crisis itself. The article hints at this universality, even if its framing is politically charged. What fascinates me is the information-theory angle. If ideologies are compression algorithms for reality, then failures are simply error signals—data that must be incorporated, not discarded. The system doesn't crash; it retrains. This is exactly how neural networks learn: through loss functions, through iteration, through failure. Maybe leftism, like a deep learning model, thrives precisely because its errors keep it from overfitting to an unchanging world. Of course, this speculative framing doesn't resolve the political debate—it just reframes it. But that's the beauty of looking at human affairs through a scientific lens: we stop asking "who's right?" and start asking "what kind of system are we?" The answer, as always, is stranger than we imagined.