Models

Sometimes Dr. Lenny will use a word in a context that he understands, but the general public will flash to a different, more comfortable meaning of the word that implies something not meant. Such be the case for the word model - which apparently isn't any longer defined as an image or projection to simplify a real world analysis.

Growing up we all built models - the cars or rocket or other things that were a kit that included all the pre-fitted parts for a '69 Chevy or Saturn booster. We knew that we were not building an actual functional '69 Chevy - but we got most of the pieces to fit where they belonged and tossed out the ones that didn't fit cosmetically. Nobody pretended that the model could work under real world conditions.

We also developed the image of a super-model, a stunning woman that jane every-girl could grow up to be. The barbie doll mentality developed, an oddunderstanding of what it took to be feminine: it was a marketized picture of shopping and house-keeping that feminists correctly identified and then blew the solution. It set back women being taken seriously in the work-place and never really touched the glass ceiling, unless the gals played dirty like at H-P.

Dr. Lenny grew up in a laboratory building model systems for protein and enzyme metabolism. The idea was to eliminate all the non-essentials from the chemical structure package, and still have the system produce the 'natural' chemistry in a laboratory. This involved removing oxygen from the system and setting things up so that the addition of oxygen resulted in unique chemisty - different from the normal products carried out under laboratory conditions. The two pieces of graduate work that composed Dr. Lenny's doctoral thesis were to build model systems that encourged the organic oxidation of sulfur to non-sulfate products and to stabilized iron in two distinct oxidation states within the same chemical compound. So the model could function chemically under pre-arranged conditions that were not duplicated in nature was a readily understood given.

Now, with the proliferation of science based on model system, everybody seems to forget that the assumptions with-in the model are not validated and often false. This is not because anybody is trying to hide anything - it is because unless we define the parameter and control it out of the model by demonstrating a known effect. We cannot tease information out of the model to have it become a better replication of the system that is, unless we reduce the number of variables. In other words - we falsely hold some parameters constant in the experiment, so that we can see the effects of other parameters.

By taking models on topics like global climate change to be absolute statements of truth and falsehood is complete nonsense. Scientists are guilty of providing information that support the point of view of their employer throughout history. That bad science generally gets culled by non-replication, while the fundamental truths reenforce themselves across the fields of discovery is part of the process. But when the profit motive takes promising science off the table, and does not allow for proper vetting and testing of the models, by making the costs and logistics of that replication unattainable, we lose the value of science and have a system that is better called applied engineering.

The question is where the science got jobbed - so that mistruths and non-truths became taught as gospel and how that developed into a system that has fundamentally ground science to a halt. We no longer wonder about how things work - we wonder how we can make a buck exploiting how things work. So our models developed in past ages are too simplistic for actually describing the phenomena that we are witnessing. But we believe in our models as reality without ascribing the diligence to compare the theory with the reality - to test the assumptions and relieve the system of the artificial restraints imposed by controlling most of the variables.

So how do we start to learn good science? When we start to question the assumption and make the comparisons. When we observe reality and make models that represent systems - not models that are systems in themselves, that are flawed from the start.

Thanks for staying with this rant - it was not an easy concept to swallow. It took many model systems to understand how model systems work. I have a model for models, but too often i talk to myself. Does this make any sense?