It's a delicate balance. We want communities to trust, respect, and understand science. But science is a method, a process. The people who practice it are fallible. The results they produce are provisional and incomplete (at best) or flat-out wrong (at worst). 

How can people honestly trust a method that, by design, changes its collective mind? How can people honestly respect a process that is, by design, more often wrong than right? How can people honestly understand a philosophical approach that, by design, steeps itself in arcane mathematics and jargon?

Let's start with trust. When we ask people to "trust" a particular scientist or result, we need to make sure that it's not the person itself that is necessarily deserving of trust, but the method and structures that they represent. Through painstakingly meticulous work, agonizingly slow timescales, and incessant revisions we come to ever more-refined descriptions of the world around us. And that is worthy of trust. Only when a particular result is placed in the proper context - motivations, current knowledge, scope of limitations, etc. - can we show communities what it means to trust scientists.