Interlibrary Loan Rates for Academic Libraries in the United States of America Have Increased Despite the Availability of Electronic Databases, but Fulfilment Rates Have Decreased
Notice bibliographique
Résumé
Objectives – To determine the number of interlibrary loan (ILL) requests in academic libraries in the United States of America over the period 1997-2008, and how various factors have influenced these rates. These factors included electronic database subscriptions, size of print journal and monograph collections, and the presence of link resolvers. Data were collected from libraries as both lenders and borrowers. The study also looked at whether the number of professional staff in an ILL department had changed during the period studied, and whether ILL departments led by a professional librarian correlated positively with rates of ILL. Design – Online questionnaire. Setting – Academic library members of the Online Computer Library Center (OCLC) ILL scheme in the United States of America. Subjects – A total of 442 academic library members of the OCLC ILL scheme. Methods – An electronic questionnaire was sent to 1433 academic library member institutions of the OCLC ILL scheme. Data were collected for libraries as both lending and borrowing institutions. Data were analyzed using a statistical software package, specifically to calculate Spearman’s rank correlations between the variables and rates of ILL. Main Results – Responses to the electronic questionnaire were received from 442 (31%) academic libraries. There was an overall increase in the number of ILL requests in the period 1997-2008. The number of ILL requests which were unfulfilled also increased during this period. There was a positive correlation between rates of ILL and all of the variables investigated, with the strongest correlations with size of print monograph collections and size of print journal collections. The numbers of staff in ILL departments remained relatively static during the period covered by the study, although the majority of staff working in ILL was composed of paraprofessionals. There was a weak positive correlation between numbers of ILL requests and whether ILL departments were headed by a professional librarian. Conclusions – Access to full text electronic databases has not decreased the numbers of ILL requests in academic libraries in the United States of America. In fact, ILL requests have increased, probably due to the fact that students and staff of academic libraries now have access to a larger number of citations through online databases and other information sources. The authors suggest that the increase in unfulfilled ILL requests is also due to this increased access. Libraries with large print collections are more likely to receive ILL requests precisely because they have more material to lend out, and may make more ILL requests due to the research output of their presumably larger institutions. There may be a higher number of ILL requests fulfilled by departments headed by a professional librarian because a librarian has more knowledge of sources to fulfil requests.
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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 | 0,003 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,004 | 0,007 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,018 | 0,005 |
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 ».