"Truth is not revealed; it is discovered. And in this process, anything goes."
We use observations to shape or formulate a concept; while on the other hand, we use a concept to shape the nature of future inquiries or observations of reality. Under these circumstances, a concept must be incomplete since we depend upon an ever-changing array of observations to shape or formulate it. Likewise, our observations of reality must be incomplete since we depend upon a changing concept to shape or formulate the nature of new inquiries and observations.
“If one’s understanding is always imperfect, it cannot be committed to print because revision is imminent”. The accurateness of one’s storytelling becomes less important that the purpose of the story itself: moving forward in the infinite and mutually influencing loop of observation and conceptualization.
CF: https://www.ribbonfarm.com/2018/01/18/the-unapologetic-case-for-bullshit/
Showing posts with label truth. Show all posts
Showing posts with label truth. Show all posts
Friday, January 19, 2018
Saturday, January 17, 2015
How To Find The Truth (on the Internet)
I recently read about two different meta-review techniques: the Total Evidence Approach and the Quality Analysis Method, and that got me thinking about information processing and knowledge creation in our information-saturation internet-era. How do we find the truth on the internet?
"In the total evidence approach (Kluge 2004; Sherman et al. 2008) all information is considered and data are not weighed by quality of evidence. Although the total evidence approach is subject to the biases and errors of individual studies, we deemed it preferable to the alternative “quality analysis” method (Sherman et al. 2008) in part because of the difficulty of objectively evaluating the relative validity and quality of the widely heterogeneous data sets that we reviewed." Source.
I think we can all agree that a total evidence approach isn't going to work very well on the internet: there is simply way to much junk to try to average out truth from the hubbub. But how to engage a quality analysis? Michelle Nijhuis describes an iterative process of fact-checking in journalism, wherein she continually seeks out new sources to comment on and counterbalance other sources, until ideally, after an infinite(!) number of steps, truth is reached asymptotically. But she admits this approach is time-intensive and unwieldy. Furthermore, this approach can lead to the problem of "false objectivity": journalists actively obscure truth when they try to objectively treat controversial issues by giving crackpots equal weight with experts and scientists.
Instead, I use a balance of evidence approach to truth-finding in science debates: I read widely and then select trustworthy sources. If a person or organization publishes unsupported or erroneous information, I tend not to give them a second chance. Also, sources that don't include open debates are outed as substandard information sources and discarded from the analysis. A process of winnowing results, and after several months (years) of research, only the best sources are left standing.
Typically, the best sources are: experts who publish in-depth analyses of primary sources (e.g. journal articles). They are open to quality comments from a range of voices, and their work is therefore continually self-correcting.
Interestingly, I often prefer blogs over than traditional journals in my research. Bloggers can attain higher standards of truth than the peer-review system. Journals are slow to correct mistakes and often don't include enough discussion to reveal divergent viewpoints.
"In the total evidence approach (Kluge 2004; Sherman et al. 2008) all information is considered and data are not weighed by quality of evidence. Although the total evidence approach is subject to the biases and errors of individual studies, we deemed it preferable to the alternative “quality analysis” method (Sherman et al. 2008) in part because of the difficulty of objectively evaluating the relative validity and quality of the widely heterogeneous data sets that we reviewed." Source.
I think we can all agree that a total evidence approach isn't going to work very well on the internet: there is simply way to much junk to try to average out truth from the hubbub. But how to engage a quality analysis? Michelle Nijhuis describes an iterative process of fact-checking in journalism, wherein she continually seeks out new sources to comment on and counterbalance other sources, until ideally, after an infinite(!) number of steps, truth is reached asymptotically. But she admits this approach is time-intensive and unwieldy. Furthermore, this approach can lead to the problem of "false objectivity": journalists actively obscure truth when they try to objectively treat controversial issues by giving crackpots equal weight with experts and scientists.
Instead, I use a balance of evidence approach to truth-finding in science debates: I read widely and then select trustworthy sources. If a person or organization publishes unsupported or erroneous information, I tend not to give them a second chance. Also, sources that don't include open debates are outed as substandard information sources and discarded from the analysis. A process of winnowing results, and after several months (years) of research, only the best sources are left standing.
Typically, the best sources are: experts who publish in-depth analyses of primary sources (e.g. journal articles). They are open to quality comments from a range of voices, and their work is therefore continually self-correcting.
Interestingly, I often prefer blogs over than traditional journals in my research. Bloggers can attain higher standards of truth than the peer-review system. Journals are slow to correct mistakes and often don't include enough discussion to reveal divergent viewpoints.
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