Volume 21, numéro 3, 2026

EN :

Objective – This research investigates how well non-local chat reference operators perform in their work with local library patrons at an R1 academic institution in the United States. More specifically, the authors sought to learn how this particular reference librarian population (co-op librarians) handled circumstances surrounding when to create a ticket for a transaction and which positive reference strategies were not utilized that should have been. In addition, the researchers rated the co-op librarians’ overall success in answering local reference questions and the kinds and frequency of false or incorrect information that was offered. Finally, the authors used the length of the reference transaction (by time and message count), reference query type, medical/health related questions, and patron satisfaction (both rater perceived and patron self-reported) as variables to learn more about situations where co-op librarians were more and less successful.

Methods – The researchers examined one year’s worth of co-op librarian chat reference records from April 2023 to March 2024. The authors created a rating form to capture structural session information like the length of the transaction, transaction day of week/time, query type, if a ticket was created, and patron self-reported satisfaction. In addition, the form solicited subjective assessment information from the researchers covering the topics detailed in the “Objective” section above. The researchers tabulated aggregated frequencies across the data produced, in addition to running a number of tests for statistical significance.

Results – The researchers were surprised to see that about one third of co-op librarian transactions happened during times when local librarians were scheduled to be available to answer these questions. They also predicted that co-op librarian performance would decline when faced with medical/health questions, but largely that was not the case. It was discovered that co-op librarians made referrals about one third of the time, and that among the two thirds that were not referred, about one third of those should have been. Overall, co-op librarians were rated as highly successful with about three quarters of their transactions in the top two of a five-point rating scale.

Conclusion – A number of overarching conclusions arose from this study, each with implications for chat reference practice. co-op librarians perform well overall, despite the challenges of frequently receiving questions with local aspects. They serve as a good backup for local librarians when the latter miss or are too busy to pick up chats. They do not shy away from attempting to answer questions, largely employ best practices in their work, infrequently inject false information into transactions, usually garner high patron satisfaction levels, and most importantly are largely successful in answering patron questions. The main struggles co-op librarians have involve dealing with account and interlibrary loan focused questions, and they also could be making referrals/tickets more frequently.

EN :

Objective – This exploratory study examines changes in traffic to academic library research guides in the early generative AI era by investigating overall traffic trends, measuring differences in usage before and after the launch of ChatGPT in November 2022, and examining changes in the referral sources that direct users to the guides.

Methods – A quantitative analysis of web traffic to the University of Ottawa Library’s LibGuides (2016-2025) was conducted to examine changes over time. Pre- and post-ChatGPT usage was compared across two equivalent 37-month periods. Google Analytics referral data (2023-2025) were analyzed to identify traffic sources and assess changes in access pathways. All analyses were conducted using RStudio.

Results – Research guide usage increased steadily from 2016 to 2022 but began declining in 2023, despite continued growth in the number of published guides. Of the 210 guides analyzed across equivalent pre‑ and post‑ChatGPT periods, most (175) experienced decreased traffic, with changes ranging from −91.3% to +462.7% and a median change of −38.35%, indicating highly variable but predominantly downward usage patterns. Although a small subset of guides (35) saw notable increases, overall engagement declined year over year. Google remained the dominant referral source, but traffic originating from Google also decreased over time, while referrals from generative AI platforms showed steady growth, alongside typical seasonal academic fluctuations.

Conclusion – Use of research guides seems to have declined since the emergence of generative AI, mirroring broader reductions in web traffic and click‑through behaviour associated with AI‑generated summaries. By empirically documenting this overall pattern within an academic library context, this study provides a necessary baseline for understanding how generative AI may be reshaping discovery pathways. Although some guides demonstrated increased engagement, the prevailing trend suggests reduced visibility and shifting access routes in an AI search environment. These findings underscore the importance of reassessing the role and discoverability of research guides for contemporary information-seeking practices.

EN :

Objective – To map how public libraries in Indonesia support the social inclusion of older adults and to identify lessons applicable to other resource-constrained settings.

Methods – This study used a scoping review design guided by established scoping review frameworks and reported according to PRISMA-ScR. Searches were conducted in DOAJ, Scopus, and Web of Science, and supplemented with targeted searches of Indonesian institutional repositories. Publications from 2014 to 2025 were screened using predefined eligibility criteria. Fifteen studies were included. Data were charted and synthesized thematically to identify service models, engagement modes, and recurring constraints and enablers.

Results – The included studies report five service models: community-based programs; intergenerational and collaborative initiatives; tailored age-friendly services; outreach and home-based provision; and assisted digital inclusion. Older adults’ engagement is described in four modes: as participants, peer mentors or facilitators, co-designers or evaluators, and outreach users requiring support. Common constraints include limited funding and staffing, accessibility gaps, digital divides, geographic inequality, and weak documentation and evaluation. The most consistent enablers are cross-sector partnerships (e.g., with primary health care, local government, and community organizations), volunteer involvement, and strong community networks. The synthesis informs a conceptual framework for age-friendly library services and a set of practice-oriented principles for local adaptation.

Conclusion – Evidence from Indonesia suggests that inclusive services for older adults are more likely to be sustained when they are partnership-based, community-anchored, and supported by outreach and assisted digital access. More consistent documentation and outcome reporting are needed to strengthen the evidence base and improve transferability to other low-resource settings.