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Historical sociologists have recently begun theorizing the archive as a field site. Building on this perspective, we offer a strategy for modeling archival encounters. This approach involves reconstructing the archive as an artifact of organizational self-representation rather than a passive repository. Our method progresses in a seven-stage computational pipeline—from scanning to metadata extraction—applied to 7,719 pages of U.S. National Archives records from the Public Health Service’s (PHS) Air Pollution Engineering Branch (1955–1962). Our findings suggest that “archival shadows” may stem from 1959 filing shifts in the National Archives, 1950s bureaucratic priorities, or our own selection biases. This “distant reading” approach provides a categorical foundation that complements more conventional “close readings.” By mapping the granular shifts in the PHS’s internal filing practices, we show that computational modeling can reveal the conditions that produced the archive itself for qualitative interpretation. We contribute a toolset for archival researchers to ground sociological questions in the text’s materiality and the procedural logic of the record-keeping system.