Analysis of Print and Electronic Serials’ Use Statistics Facilitates Print Cancellation Decisions
Bibliographic record
Abstract
A review of:
 
 Gallagher, John, Kathleen Bauer, Daniel M. Dollar. “Evidence-Based Librarianship: Utilizing Data From All Available Sources to Make Judicious Print Cancellation Decisions.” Library Collections, Acquisitions & Technical Services 29.2 (2005): 169-79.
 
 Objective – To apply the principles of evidence-based librarianship to the decision-making process regarding the cancellation of print serials.
 
 Design – Quantitative analysis of local and national data from various sources.
 
 Subjects – Data sources included 1249 current unbound print journals, 3465 Medline-indexed electronic journals, statistics from the Association of Research Libraries and American Association of Health Sciences Libraries, as well as traditional library statistics.
 
 Setting – The study was conducted in the Yale University’s Cushing/Whitney Medical Library located in New Haven, Connecticut U.S.A.
 
 Methods – Several sources were targeted for data. A three-month periodical usage study of the current issues of the library’s 1249 actively received print titles was undertaken. Excel-generated alphabetical listings of titles were used by shelvers to indicate, with a check mark, which issues were shelved during a specified week. The workflow was adjusted to ensure only items under study were counted. Signs asking patrons not to re-shelve journal issues were posted. Usage data were collected weekly and entered into an Excel spreadsheet where the total use of the journals was tracked. In-house circulation, photocopy, and gate count statistics were also used. In addition to the survey, SFX statistics for the library’s electronic journals indexed in MEDLINE (3465) were gathered during the same 3 month period covered by the print usage survey. MEDLINE was chosen as the delineating factor to ensure consistent subject coverage with the print journal collection. For perspective and trends, statistics from the Association of Research Libraries and the American Association of Health Sciences Libraries were considered.
 
 Main Results – Based on the study’s findings, 53% of the print collection (657 titles) received no use during the study period; 7.1 % (89 titles) were used more than once per month; and 1.28% were used one or more times per week. Further, only 10% (125 titles) of the collection represented 60.7% of the total print collection use. There was also a direct correlation between the drop in patrons coming to the library and the decrease in print periodical use. SFX statistics revealed that of the 3465 MEDLINE indexed titles 14.8% (513 titles) were not accessed at all and 10% of the journals represented 56.8% of all SFX usage. These results were consistent with statistics from the Association of Research Libraries and the American Association of Health Sciences Libraries.
 
 Conclusion – Titles that were used the most in print were also used the most electronically. Further, the study revealed that print journals are used only a fraction as often as their electronic counterparts. Indeed, in both the case of print and electronic journals the largest use came from a small number of subscribed titles. Print collection maintenance is more labour intensive and costly than electronic. Consequently, resources spent supporting 53% of the print collection that is not used seriously impacts efficiency. With constraints on acquisitions budgets, funding unused collections does not make sense. Examination of the print serial collection is only part of ensuring effective collections. As this study has indicated, unused electronic titles are also a drain on resources and further analysis of electronic packages is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.169 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; both teacher heads agree on what is shown here.
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".