week 1 blog reflection
Steven Allers - Reflection One
Tallbear’s paper is a declaration of the indignation of indigeneity. In it, they explain how attempting to categorize tribes by haplotypes, in essence, genetically stereotypes the tribes by their genetic novelty. For instance, a person of a tribe not containing the prerequisite distinctness of said haplotype, perhaps through mixed genetic parentage, would in such a definition not be ‘indigenous’, despite being fully recognized by their tribe. This is additionally problematic in that the classification and distinction of said haplotypes is largely decided by non ‘indigenous’ people. Tallbear further explores this idea of modification by identification; in classifying and labeling ‘their’ world, colonial Europeans have constructed a system which, to its very etymological core, implies European sovereignty. For instance, even in the name ‘First People’ or ‘First Nations’, the colonial implication is that such people were a precursor, or historical artifact – most importantly, again, the are a novelty. However, Tallbear testifies that modern Native people are not so monochromatic; their culture is very much evolving, living, and, despite contrary popular belief, growing.
The eDNA review paper is, besides being a great overview, also an excellent guide for potential troubleshooting. Very much practical, the review is not just designed with the intent of not just recapping and offering guidance for future work, but offers insights, practice tips, and cautions for current eDNA work. The paper also offers varied information, from perspectives on collection, all the way to information on post-collected analytical processes. This paper could be useful for almost anyone within the Maine eDNA group. There are only two caveats; the first of which is that the paper being in 2018 seems to be slightly before or perhaps during the period in which the mitofish 12s primers were designed, which I believe the eDNA group has an interest in using, and the capabilities and accuracies of which may be different than the analyzed 16s/18s primers discussed. The second, not really a caveat, but more of a thought; there is also little mention in terms of future directions of machine learning and AI work. In terms of taxonomic and bioinformatics, this is a huge element. In fact, the current pipeline I work on uses DADA2, which as far as I know is a machine learning clustering algorithm that appears to be quite robust. The prominence and potentiality of machine learning may have deserved its own paragraph, as its continued development may radically impact bioinformatics across the board.