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Some Basic Concepts in System Dynamics - Creative Learning ...

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D-4894 - 11 -<strong>in</strong> skilled labor; and, furthermore, no charge was assigned so it costnoth<strong>in</strong>g.The perfect job-tra<strong>in</strong><strong>in</strong>g program caused unemployment <strong>in</strong> themodel to go up. The <strong>in</strong>crease <strong>in</strong> unemployment surprised me until Ispent a day discover<strong>in</strong>g what the model was do<strong>in</strong>g, after which theresult seemed plausible. I took the computer runs back to formermayor John Coll<strong>in</strong>s and the several people from Boston bus<strong>in</strong>ess andpolitics that had been work<strong>in</strong>g with me. They looked at the ris<strong>in</strong>gunemployment as a result of <strong>in</strong>troduc<strong>in</strong>g job tra<strong>in</strong><strong>in</strong>g <strong>in</strong> silence forseveral m<strong>in</strong>utes until one said, “Oh, Detroit has the best job-tra<strong>in</strong><strong>in</strong>gprogram <strong>in</strong> the country and the most rapidly ris<strong>in</strong>g unemploymentrate!” Later I went to people <strong>in</strong> the bus<strong>in</strong>ess of runn<strong>in</strong>g job-tra<strong>in</strong><strong>in</strong>gprograms and asked if they had ever heard of a situation where jobtra<strong>in</strong><strong>in</strong>g could <strong>in</strong>crease unemployment. Their answer, “Of course,when that happens we go to another city.”The job-tra<strong>in</strong><strong>in</strong>g program <strong>in</strong> the model was defeated by threeforces: 1) before the program, bus<strong>in</strong>esses had been dipp<strong>in</strong>g <strong>in</strong>to theunskilled and unemployed pool as necessary to obta<strong>in</strong> employees.The job-tra<strong>in</strong><strong>in</strong>g program substituted for the tra<strong>in</strong><strong>in</strong>g that bus<strong>in</strong>esseswould have done, so tra<strong>in</strong><strong>in</strong>g by bus<strong>in</strong>esses stopped. About half of thetra<strong>in</strong><strong>in</strong>g program was neutralized by such substitution; 2) the program<strong>in</strong>creased the number of skilled workers thereby <strong>in</strong>creas<strong>in</strong>gunemployment among skilled workers and resulted <strong>in</strong> <strong>in</strong>creaseddownward flow back to the unskilled-unemployed pool. Nearlyanother half of the tra<strong>in</strong><strong>in</strong>g was lost through the <strong>in</strong>creased downwardmobility; 3) and last, the tra<strong>in</strong><strong>in</strong>g program had high public visibilityand attracted unemployed from other cities, even though the programhad not created significant new jobs. Forces with<strong>in</strong> the systemneutralized the tra<strong>in</strong><strong>in</strong>g program and the public visibility of theprogram attracted additional people who would <strong>in</strong>crease unemployed.Another situation of first learn<strong>in</strong>g about real life from a simulation modelarose when a student modeled the behavior of <strong>in</strong>sul<strong>in</strong> and glucose <strong>in</strong> variousaspects of diabetes. In response to an experiment simulated with<strong>in</strong> the model, hegot a result from his computer patient that had never been reported <strong>in</strong> the medicalliterature. Was there someth<strong>in</strong>g wrong with the model? He showed the results todoctors do<strong>in</strong>g diabetes research. After study<strong>in</strong>g what was happen<strong>in</strong>g <strong>in</strong> the model,their response was, “We had a patient like that once, but always thought there was

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