Impressed by the quality of some replies of yours regarding the post “Power of Words” and quoting Marcial Losada’s groundbreaking research, I went to him directly and asked to comment and summarize his work for our mutual benefit. Marcial was kind enough to respond and here it is:
“For the benefit of the readers who are not familiar with Meta-Learning (ML), here is a very brief introduction. ML has three variables (dimensions) and 3 parameters. The variables are inquiry-advocacy, positivity-negativity (P/N), and other-self (or external-internal orientation). The three parameters are connectivity (the critical, control parameter), negativity bias and resistance to change (system’s viscosity). The model is driven by a set of nonlinear differential equations that have the same mathematical structure as the Lorenz model (the one that generates the famous butterfly-shaped attractor and is used in many branches of science). ML accounts for 92% of variance in a system’s (couple, team, organization) performance. The best linear models only account for 30% of that variance.
A team is most successful when its members are well connected, is able to balance external vs. internal orientation as well as inquiry and advocacy, and keeps a P/N ratio within the Losada Zone (greater than or equal to about 3:1 and not more than about 11:1). We have taken measurements all the way from Finland to the Patagonia (where there is Methanex, one of the world’s largest methanol company) and I have never observed a team which reaches a 6:1 ratio (5.6 is the upper limit so far). In the Losada Zone, a team is able to flourish (and earn a lot of money as a side bonus) and to be “in the flow” (time doesn’t seem to go by and creativity thrives). Out of the zone, a team languishes visiting over and over the same old routines that keep them stuck, without ever getting to know the best of themselves. This is very sad and it is the main reason why I started a consulting business. I wanted to stop the pain (and make money as a bonus).
Marvin and Michael speak about the power of words and specifically about how, when those words are at least in a P/N ratio of 3:1, we find the best of ourselves. The power of language is indeed something that deserves our attention. Wittgenstein saw it as a prison. And he was right, because language can imprison us. There are two types of prison in nonlinear dynamics: fixed-point attractors and limit cycles. We get there when our P/N ratio (and the words that go with it) are outside the Losada Zone. But language can also liberate us (and Wittgenstein also saw this; he was no fool). Meta Learning is a liberating process whereby we dissolve limiting dynamics such as limit cycles and fixed points and evolve complex order dynamics (that I call complexors–complex order). Lorenz’s butterfly is a complexor and my high performing teams all have butterfly-shaped trajectories when I look at their interaction behavior in phase space. When we are in a complexor pattern we accomplish a great feat: we learn who we truly are and what we are capable of doing. Once you taste this fruit, you are able to transform knowledge into wisdom. You are in a kind of paradise from where you will not be expelled, unless you do that to yourself. When my high performing teams reach a complexor they stay there. I have measured them years later and they are still there. Sustainability is one of the greatest benefits of the training provided by the ML methodology.
I must end by saying that the power of words when viewed from the P/N ratio is much more that what we ever imagined. There is a fascinating study by Dr. Grazyna Rajkowska with chronic depressive patients who lose cerebral mass in the prefrontal cortex and hypothalamus. It turns out that the average chronic depressive has a P/N ratio of 0.5 (two negatives for every positive). I discovered a mathematical function that I call “gamma function” which links P/N to gains or losses in a system. The gamma function predicts a 30% loss of cerebral mass in chronic depressives. This prediction was corroborated by Dr. Rajkowska who measures the loss quite precisely using laser interferometry.
I find this astonishing. How can it happen? What is the mechanism by which P/N destroys cells if it is too low? In my view, the explanation goes back to Einstein formula relating energy to mass. To act on the cerebral mass we need energy (or lack of it to feed those cells in the case of depressives). When you look at the P/N pattern over time, you realize it is an oscillatory pattern, a vibrational pattern. Hence an energy pattern; its frequency increases as the P/N ratio does. This being so, we should also be able to predict the opposite effect: a gain when the P/N ratio is above the Losada Line (3:1). Richie Davidson did a famous study published in the Proceedings of the U.S. National Academy of Science on Tibetan monks doing loving-kindness meditation whose P/N ratio is 4:1 as shown by the differential activation of their left and right prefrontal cortex. My gamma function for that ratio predicts a gain of 30%. Richie discovered that gamma synchrony in the monks is increased by about 30%. Gamma waves are the fastest (higher frequency, hence higher energy) and they connect different parts of the brain which makes creativity and intuition available to us. In this case the gain is not so much in cerebral mass as it is on connectivity. I have shown in my paper, The Role of Positivity and Connectivty in Business Teams, that connectivity and the P/N ratio are mathematically equivalent. This might be the explanation at the brain activity level of Barbara Fredrickson’s findings that P/N broadens our thought-action repertoires.
So watch those words! You might be increasing (or decreasing) your cerebral mass. Perhaps we can start our next team meeting with a mission statement: let’s not lose cerebral mass today!”