Notice bibliographique
Résumé
Introduction: In recent years, the cancellation of so-called journal ‘big deals’ has gained attention and traction within librarianship. In March 2019, University of California’s termination of its $11 million USD/year contract with Elsevier made headlines around the world and was seen by many as a turning point in scholarly publishing and the open access movement. Less attention has been paid, however, to how the potential cancellation of other high-value bundled resources is being handled by libraries. This lightning talk will detail the process undertaken at one health sciences library to assess cancelling its subscription to ClinicalKey, including usage analysis, acquisitions and negotiation strategies, and communications rollout. Description: Owned by Elsevier, ClinicalKey is a key online resource within the health sciences, with a primary focus on medical clinicians; it contains ~550 journals, ~690 electronic books, procedural multimedia, and point of care resources. The University of Manitoba subscribed to ClinicalKey when it launched in 2012, but rising subscription costs, budget constraints, and increasing restrictions placed on how patrons could access content contributed to the need for a thorough assessment as a continued subscription became increasingly unsustainable. Further complicating the process, key texts available only through ClinicalKey are still used as required texts throughout the medical school curriculum so access to a large number of books would need to be renegotiated on a stand-alone basis. Outcomes: Usage stats show that the primary use of ClinicalKey is its books, especially textbooks used by UGME and PGME medicine. Some titles were used more than 1000 times in 2019 alone and cost per use figures show high value for dollar. Replacement costs for only the most used books would cost roughly 78% of an annual subscription to the full package, and would offer significantly reduced access to content. Over 30% of the most used titles are not available electronically. While much of the journal content is covered through overlap subscriptions, the cost to replace the 11 unique titles is still significant. Discussion: It is estimated that cancelling ClinicalKey and only buying back the most used content would cost ~75-80% of our annual renewal cost, and would lead to a decrease in access (i.e., number of seats). In part we were hampered by high costs for a la carte purchases, and many titles that are simply not available electronically. COVID-19 was also a factor in the decision-making process, as restricting access and requiring program coordinators to choose new textbooks during a pandemic would have been inadvisable. While the decision was made to renew ClinicalKey, broader discussions need to be had whether libraries should support what is essentially an online textbook resource. ‘Big deal’ discussions also need to more broadly include monograph packages, which are inherently different, and we would argue more complicated, from cancellation of journal packages.
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 | 0,025 | 0,113 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,006 | 0,009 |
| Études des sciences et des technologies | 0,005 | 0,005 |
| Communication savante | 0,022 | 0,024 |
| Science ouverte | 0,002 | 0,013 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,132 | 0,069 |
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 ».