The Impact of Off-Site Storage on Core Special Collections Activities
Bibliographic record
Abstract
A Review of: Priddle, C., & McCann, L. (2015). Off-site storage and special collections: A study in use and impact in ARL libraries in the United States. College & Research Libraries, 76(5), 652-670. doi:10.5860/crl.76.5.652 Abstract Objective – To measure the use of off-site storage for special collections materials and to examine how this use impacts core special collections activities. Design – Survey questionnaire containing both structured and open ended questions. Follow-up interviews were also conducted. Setting – Association of Research Libraries (ARL) member institutions in the United States of America. Subjects – 108 directors of special collections. Methods – Participants were recruited via email; contact information was compiled through professional directories, web searches, and referrals from professionals at ARL member libraries. The survey was sent out on October 31, 2013, and two reminder emails were distributed before it closed three weeks later. The survey was created and distributed using Qualtrics, a research software that supports online data collection and analysis. All results were analyzed using Microsoft Excel and Qualtrics. Main Results – The final response rate was 58% (63 out of 108). The majority (51 participants, or 81%) reported use of off-site storage for library collections. Of this group, 91% (47 out of 51) house a variety of special collections in off-site storage. The criteria most frequently utilized to designate these materials to off-site storage are use (87%), size (66%), format (60%), and value (57%). The authors found that special collections directors are most likely to send materials to off-site storage facilities that are established and in use by other departments at their home institution; access to established workflows, especially those linked to transit and delivery, and space for expanding collections are benefits. In regard to core special collections activities, results indicated that public service was most impacted by off-site storage. The authors discussed challenges related to patron use and satisfaction. In regard to management and processing, directors faced challenges using the same level of staff to maintain two locations instead of one. Also, the integration of new workflows required additional oversight to ensure adequate control at all points of process. Static staffing levels and increased levels of responsibility impacted preservation and conservation activities as well. A central concern was the handling of materials by facility staff not trained as special collections professionals. In regard to the facilities themselves, a general concern was that commercial warehouses do not always provide the kind of environmental control systems recommended for storage of special collections materials. Of the total sample group, 12 participants (19%) said their institution does not use off-site storage for special collections. When asked if this may occur in the future, four directors (33%) said they anticipate off-site storage use within the next five years. Lack of space was listed as the primary motivation. Conclusion – Study findings provide evidence for what was previously known anecdotally: planning, coordinating, and managing off-site storage is a significant professional responsibility that will only grow in the future. As primary resources are integrated into research, teaching, and learning activities, the acquisition of special collections materials will continue to grow. Discussions regarding off-site storage workflows and strategic planning will continue as professionals seek compromises that meet the unique needs of acquisition, preservation, and public service.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.035 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".