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Close - Hyper - Machine reading

N. Katherine Hayles

Related to the idea of pattern is the question of meaning. Since entire books have been written on the subject, I will not attempt to define meaning but merely observe that wherever and however it occurs, meaning is sensitively dependent on context. The same sentence, uttered in two different contexts, may mean something different in one than in the other. Close reading typically occurs in a monolocal context (that is, with a single text). Here the context is quite rich, including the entire text and other texts connected with it through networks of allusions, citations, and iterative quotations. Hyper reading, by contrast, typically occurs in a multilocal context. Because many textual fragments are juxtaposed, context is truncated, often consisting of a single phrase or sentence, as in a Google search. In machine reading, the context may be limited to a few words or eliminated altogether, as in a word-frequency list. Relatively context poor, machine reading is enriched by context-rich close reading when close reading provides guidance for the construction of algorithms; Margaret Cohen points to this synergy when she observes that for computer programs to be designed, "the patterns still need to be observed [by close reading]" (2009:59). On the other hand, machine reading may reveal patterns overlooked in a close reading, a point we saw in chapter 2 with Willard McCarty's work on Ovid's Metamorphoses (2005:3-72). The more the emphasis falls on pattern (as in machine reading), the more likely it is that context must be supplied from outside (by a human interpreter) to connect pattern with meaning; the more the emphasis falls on meaning (as in close reading), the more pattern assumes a subordinate role. In general, the different distributions among pattern, meaning, and context provide ways to think about interrelations among close, hyper, and machine reading.