A Case Study on How Reference Staffing and Visibility Models Impact Patron Behaviors
Notice bibliographique
Résumé
A Review of: Holm, C.E. & Kantor, S. (2021). Reference is not dead: A case study of patron habits and library staffing models. Portal: Libraries and the Academy, 21(2), 299–316. https://doi.org/10.1353/pla.2021.0017 Abstract Objective – To determine if reference staffing models are a predictor of reference question rates and if academic library patrons’ reference behaviors are linked to reference staffing models and desk visibility. Design – A retrospective case study. Setting – Two academic libraries at a large R3 public university in the state of Georgia, United States of America. Subjects – 10,295 service transactions (chat and in-person, including non-reference transactions related to directional and technology questions) from the 2016 fiscal year and 6,568 service transactions (chat and in-person, including only chat non-reference transactions) from FY 2017. Methods – Analysis of two years of service transaction data (July 2015 to June 2017) recorded by librarians using the reference analytics module of Springshare’s LibAnswers at three locations (virtual 24/7 chat and two libraries with different physical locations, such as centrally-located or harder-to-find service points) for three kinds of reference service modes: chat, fully-staffed in-person services, and occasional “on-call” services. “Reference” transactions were classified using the Reference & User Services Association (RUSA) definition. Email, SMS/text, and Facebook inquiries were excluded from this study. One library, which had the same service model for the 2016-2017 fiscal years, served as the study’s “control” so that an analysis of service model alterations could be conducted.Main Results – The rate of chat reference remained steady, independent from the desk model employed. There was also an overall decline in reference questions from FY 2016 to FY 2017. For FY 2016, the average daily chat transaction rate was 16.1 inquiries (range: 0 inquiries for some days and up to 51 for others) compared to an average 20.5 inquiries at the two physical service locations (range: 0 to 95 inquiries per day). In FY 2017, the average daily chat transaction rate was 13.9 inquiries (range: 0 to 46 inquiries per day) compared to 6.8 transactions for the physical locations (range: 0 to 19 inquiries per day). For FY 2016, when the model shifted to on-call, the average daily chat transaction rate was 14 inquiries compared to the physical locations with 0 and .67 inquires per day. In FY 2017, the averages were 19.33 for chat compared to .33 and .33 for the physical locations. Conclusion – For the two fiscal years studied here, question rates and reference behaviors seemed to be linked to staffing models. Patrons in this study preferred a staffed and visible desk and 24/7 chat, while “on-call” services were not favored. By replacing the visible desk with an on-call model, the library created a situation where chat was the only consistent reference service offering. As a result, patrons may have viewed the visible desk as being unreliable. The on-call service model appears to have negatively affected patron behavior since, according to the data presented, patrons’ reference needs were best met by chat and a visibly staffed desk service model.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,002 | 0,637 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».