Before You Tell Me What You “Know,” Tell Me Your Sources, by Charles Hugh Smith

You can trust far few “facts” and much less “information” than you think, in a world where disinformation runs rampant. From Charles Hugh Smith at oftwominds.com:

We can no longer trust data and conclusions being published as impartial by institutions that were once trustworthy.
When someone says they “know” what’s happening on the ground in Syria, how can we assess the validity of their claim to knowledge, i.e. their claim to “know” “facts” or (gasp) “truth”?
When someone says they “know” the U.S. economy is growing and unemployment is at record lows, what is the basis of their claim to knowledge?
Before you tell me what you “know,” tell me your sources. We all know how this works nowadays: the sources are rigged or gamed to support the pre-selected narrative.
In “fake news,” the sources are designed to appear legitimate via official-sounding institutional titles for the source organizations and human “experts” / researchers, and the data that’s presented to support the “fake news” is also designed to be indistinguishable from legitimate data.
The cursory consumer of such content will be inclined to grant the institution, source and data as equal in legitimacy to other accepted sources. For example, if we read that the United Nations Labor Information Council has collected data showing the U.S. unemployment rate is actually 7.2% rather than the official 3.9%, the invocation of the UN and the precision of the data point suggests a legitimate source and data base.
But it’s “fake news;” there is no United Nations Labor Information Council (at least not to my knowledge).
Official sources have learned that the most effective way to propagate the sanctioned narratives is to rig or game the data and/or its interpretation. Thus the bailouts of the U.S. “too big to fail” financial institutions in 2008-09 were purposefully obscured; it took independent researchers to assemble all the bailout guarantees and publish the staggering total of over $16 trillion.
Official data is massaged to promote the official narrative. This is well-known to anyone who digs into the actual mechanics of the adjustments made to the raw data. For example, to mask real-world inflation, big-ticket expenses such as healthcare are minimized as a percentage of the basket of expenses being measured, and hedonic adjustments reduce the sticker price we actually pay.
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