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We elaborate on reasoning in contemporary (semi) automatic parallelizing refactoring. As the main contribution we summarize contemporary approaches and show that all attempts to reason in parallelization thus far, have amounted to local code analysis given data and control dependencies. We conclude that, by retaining this perspective only, parallelization continues to exploit merely a subset of the reasoning methods available today and is likely to remain limited. To address this problem we suggest to expand the local analyses, such that, they take seriously relations between individual local parallelizing transformations. We argue that such a coupling allows to process sparser parallelizable constructs, such as, producer-consumer coordination. We identify questions to be addressed to put this principle into action and report on-going work on (reasoning) mechanisms able to support this.