The Potential of a Cost-Per-Use Analysis to Assess the Value of Library Open-Access Funds
Notice bibliographique
Résumé
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).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,098 | 0,239 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,006 |
| Bibliométrie | 0,020 | 0,016 |
| Études des sciences et des technologies | 0,001 | 0,003 |
| Communication savante | 0,010 | 0,013 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».