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Enregistrement W1594598352 · doi:10.18438/b8d30h

Analysis of Print and Electronic Serials’ Use Statistics Facilitates Print Cancellation Decisions

2006· article· en· W1594598352 sur OpenAlexaffvenue
P. Edward Haley

Notice bibliographique

RevueEvidence Based Library and Information Practice · 2006
Typearticle
Langueen
DomaineComputer Science
ThématiqueLibrary Collection Development and Digital Resources
Établissements canadiensQueen's University
Organismes subventionnairesnon disponible
Mots-clésLibrary scienceMedical libraryComputer scienceWorkflowDatabase

Résumé

récupéré en direct d'OpenAlex

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.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCommunication savante
Catégories consensuellesCommunication savante
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,925
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,169
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,014
Tête enseignante GPT0,229
Écart entre enseignants0,215 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2006
Routes d'admission2
Résumé présentoui

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