Fairly early in this project, Courtney and I determined that “MPLP 2 Hours” was not going to be a wholesale success—most collections simply cannot be processed in that time frame, regardless of the shortcuts taken (our average across the board is 3.2 hours per linear foot). And in some cases, those shortcuts resulted in a product that we did not feel was more useful to a researcher post-processing. What we have determined is essentially this … it is difficult, if not impossible, to say that collections can be processed in a set or determined amount of time, but it is possible to make educated estimates allowing us to allocate human resources to process collections efficiently.
There are several factors that allow us to better determine a time frame for the processing of collections: age, type of collection, and original arrangement of the collection are the three biggies. None of these factors work independently—they are all intertwined to help determine the time frame. So, based upon the data collected for 125 collections, processors have physically processed collections with the oldest material dating from the:
17th century at an average of 4.1 hours per linear foot;
18th century at an average of 3.3 hours per linear foot;
19th century at an average of 3.4 hours per linear foot;
20th century at an average of 2.9 hours per linear foot.
Processors have processed:
artificial collections at an average of 3.6 hours per linear foot;
institutional/corporate records at an average of 2.5 hours per linear foot;
personal papers at an average of 3.7 hours per linear foot;
family papers at an average of 4.2 hours per linear foot.
Age seems like it should be the most logical factor, but in fact, it has proven to be the least certain factor in our ability to judge the time frame for processing. We thought originally that old collections (pre 1850s for certain) would take us significantly longer to process, but this is not necessarily the case. The age does not seem to deter us in being able to efficiently process an “old” collection. Age does, however, quite frequently deter us from describing the collections well. Quickly skimming for content in folders of 17th, 18th and 19th century handwritten material is not easy—and it absolutely results in less thorough description. However, if the collection is arranged and available for research use, perhaps this is where we ask for help … as researchers use the collections, we can ask them to provide more robust description of what the correspondence, journals, etc. contain. Finding aids CAN be iterative … especially with technology such as the Archivists’ Toolkit. “Newer” collections may or may not be easier to process … certainly there is more typewritten material that makes it immediately easier to categorize series/subseries/folders and describe the contents of the folders more thoroughly. However, in the end, the ease of the processing relies more heavily on the type of collection more than the age.
For this project, we have divided collections into four basic types: institutional/corporate records, personal papers, family papers and artificial collections. Again, there is no one size fits all … each collection is unique (is that not why archival collections are so awesome?). Generally speaking though, an institution or company’s records can be processed most quickly, followed by personal papers and then family papers. Artificial collections are usually the fastest or the slowest depending entirely upon the collector. Usually, they are speedy—the collector is in love with the topic they are collecting and as a result, they arrange the collection for their own personal satisfaction and use—all the letters of a children’s book author are arranged chronologically by date sent or alphabetically by the recipients’ names. If this is the case, the artificial collection is a dream to process and it usually requires only description. In a few instances, however, we have found collections where the collector simply collects … they probably know that the stuff is important, but they are not organizers. At that point, trying to create a system out of a group of randomly acquired material can be quite difficult.
Institutional and business records are usually quick and easy and this is because the functions of a business or an institution generally follow the same basic structures and are fairly predictable. Usually, you will find financial records, minutes, committee records, administrative records, subject files, correspondence, etc. Because the function generates the records, it is logical and easy to determine a good organizational scheme for the papers. But as always, the collections are unique and we have found that different creators generate different levels of tidiness, logical order, and structure.
Personal papers are the next quickest to process (generally speaking), especially if the creator was involved in several major movements, careers, and/or activities. However, the ability to efficiently process a person’s personal collection often depends upon how intermingled those pursuits are with family, friends, and work.
Family papers have been, fairly consistently, the most time-consuming collections to process. The problems that arise with family papers that generally do not exist with personal papers are the intertwining relationships that make determining to whom a certain group of materials belong challenging, and sometimes, impossible. When every generation in a family has a woman named Sarah, determining generations becomes a trial. Many a day passed at the Historical Society of Pennsylvania with the following conversation: “So wait, this is Sarah Logan Wister Starr?” “No, this is Sarah Logan Starr Blaine!” Or: “Here is a letter to Grandma Sarah from Sarah …does that mean it is Sarah Logan Starr Blain?” “No! It could be Sarah Logan Starr Blain OR Sarah Logan Wister Starr OR Sarah Tyler Boas Wister!” Egads … I wanted to buy a baby name book for this family! Not surprisingly, this kind of questioning takes time … lots of time.
The third main factor in determining time for processing a collection is existing arrangement. A collection of 20th century business records thrown into boxes will take longer than a collection of 18th century business records that are housed in volumes. A collection of family papers organized by the donor into distinct family member’s papers can probably be processed more quickly than a collection of personal papers that are completely unsorted. I have intentionally not used the term original order which implies that the order was generated the creator. Existing arrangement may have been generated by the creator, but in many cases, it is generated by an archivist who starts processing the collection but does not complete the project. Unfortunately, the hardest collections to process efficiently are often collections that someone else has started to process. Trying to understand an undocumented order that has been imposed or continue with an arrangement scheme that does not seem logical is much more difficult than imposing order from absolute chaos. And without a questions, the collections that take the absolute longest are ones in which parts of the collection have received item level treatment. Addressed in the next blog post will be how this type of existing arrangement affects description of collections.
So, basically what we have said here is that every collection is different and unique and there is absolutely no way to say that one time will work even within a date frame or a type of record. Our observations are backed by Greene and Meissner who say that “MPLP … advises vigorously against adopting cookie-cutter approaches … and [recommends] flexible approaches,” (page 176). In order to make educated estimates for allocating resources, we believe that a base-line starting time frame is needed: institutional/corporate collections should be given 3 hours per linear foot. Based upon the existing arrangement, tack on another hour per linear foot if it is in a shambles. If the bulk of the material is from the 18th century, tack on yet another hour per linear foot for increased perusal time which will result in more effective description. So, in this case, your estimated processing time is 5 hours per linear foot. Could you do it in three? Yes, probably. However, with allowances for age and existing arrangement, you will almost unquestionably have a better product, still at just over ½ the rate of traditional processing.
Based upon our experience, the PACSCL/CLIR project believes that the following base-line processing time estimates would work well:
Artificial collections: 3 hours per linear foot
Institutional/corporate collections: 3 hours per linear foot
Personal papers: 4 hours per linear foot
Family papers: 6 hours per linear foot
Our averages clearly show how quickly collections can be processed … but the base-line estimate with upgrades allows us to provide the best possible product while being mindful of available resources.