The Potential of a Cost-Per-Use Analysis to Assess the Value of Library Open-Access Funds
Bibliographic record
Abstract
A Review of: Hampson, C., & Stregger, E. (2017). Measuring cost per use of library-funded open access article processing charges: Examination and implications of one method. Journal of Librarianship & Scholarly Communication, 5(1), eP2182. https://doi.org/10.7710/2162-3309.2182 Abstract Objective – To determine the feasibility and potential effects of a cost-per-use analysis of library funds dedicated to open access. Design – Cost-per-use analysis, case study. Setting – PLOS and BioMed Central. Subjects – 591 articles published in PLOS ONE, 165 articles published in PLOS Biology, and 17 articles published in BioMed Central. Methods – Three specific examples are provided of how academic libraries can employ a cost-per-use analysis in order to determine the impact of library-based open access (OA) funds. This method is modeled after the traditional cost-per-use method of analyzing a library collection, and facilitates comparison to other non-OA items. The first example consisted of using a formula dividing the total library-funded article processing charges (APCs) by the total global use of the specific PLOS journal articles that were funded. The second and third examples demonstrated what a library-funded OA membership to BioMed Central would cost alone, and then with APCs that cost could be divided by the total usage of the funded articles to determine cost-per-use. Main Results – The authors found both of the examples described in the article to be potential ways of determining cost-per-use of OA articles, with some limitations. For instance, counting article usage through the publisher’s website may not capture the true usage of an article, as it does not take altmetrics into consideration. In addition, article-level data is not always readily available. In addition, the cost-per-use of OA articles was found to be very low, ranging from $0.01 to $1.51 after the first three years of publication based on the cost of library-funded APCs. The second and third methods revealed a cost-per-use of $0.10 using membership-only payments, while using the cost of membership plus APCs resulted in a cost-per-use of $0.41. Conclusion – Libraries may wish to consider using these methods for demonstrating the value of OA funds in terms of return on investment, as these techniques allow for direct comparison to the usage of traditional journals. However, several barriers need to be overcome in how article-level usage is obtained in order for these methods to be more accurate and efficient. In addition, while the authors report that "The specific examples in this study suggest that OA APCs may compare favorably to traditional publishing when considering value for money based on cost per use," they also caution that the study was not designed to answer the question if the ROI is greater for OA publications than for traditional articles, stating that "...the data in this study should not be interpreted as a verification of such an argument, as this study was not designed to answer that question, nor can it do so given the limitations on the data. This paper was designed to present and illustrate a method. Further study would be necessary to verify or refute this possibility" (p. 15).
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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 | 0.098 | 0.239 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".