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Investigating original order with cybernetics and community detection algorithms

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Abstract

This article is an exploration into the principle of original order and begins with the presentation of a case study, which involved subjecting the records of a single department to a series of community detection algorithms. The results of the algorithms were visualized and presented to department staff members during qualitative interviews, who were asked to decide which community detection algorithm best represented their department. The case study results, along with ideas from the field of cybernetics, placed the work of Muller, Feith, and Fruin in a new light. More specifically, it became clear that the principle of original order and the principle respect des fonds crucially result in aggregates comprised of mutually relevant records. This mutual relevance is a necessary feature of an archival aggregate, as it makes it possible for researchers to corroborate pieces of data, which in turn enables a reconstruction of the past. Ultimately, this article delves into the various ways that record aggregates become mutually relevant, investigating physical original order, administration-based original order, and functional classification.

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Notes

  1. This project was approved by the Behavioural Research Ethics Review Board at the University of British Columbia on 23 October 2015. To avoid jeopardizing the anonymity of the study participants, several measures have been taken: details regarding the department have been withheld, individual participants are referenced via aliases, and the name of documents has been replaced with fictional names.

  2. With the exception, that is, of the September–December 2015 visualization where the node on the far right is shown isolated from the rest of the department. As almost all interviewees noted, this is because the person represented by the node was transitioning out of the department into a sister department.

  3. During the interviews, the visualization was not displayed as it is in Fig. 1: I made a mistake coding the last two visualizations of Edge-betweenness. Once corrected, it was clear that the September–December 2015 visualization of the Edge-betweenness algorithm clearly displayed the administrative subgroups referenced during interviews. Given this, it is possible that more interviewees would have chosen Edge-betweenness as the most representative visualization of their organization, had it been visualized properly.

  4. It should be noted that the term 'archival collection' is widely considered a poor translation of Muller, Feith, and Fruin’s term for an archival fonds, “archief.” This is because “collection” connotes a groups of records brought together artificially by a collector, which jars with the definition of a fonds as the related records belonging to a single creator (Horsman et al. 2003, p. 30).

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Acknowledgements

I am grateful for the ideas and guidance of Dr. Jennifer Douglas, Dr. Giovanni Michetti, and Dr. Luanne Freund, who encouraged my interests and helped me refine my thinking. I am also indebted to the interviewees whose insights form the basis of this work, and specifically the manager who permitted the project to take place in his department. Information Technology professionals Matthew Ellis, Sherryll Catindig, Waii Chow, and Michael LeBlanc generously developed the script that made the project possible.

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Correspondence to K. S. Chandler.

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Chandler, K.S. Investigating original order with cybernetics and community detection algorithms. Arch Sci 17, 267–283 (2017). https://doi.org/10.1007/s10502-017-9276-1

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