Reference Chatbots in Canadian Academic Libraries
Bibliographic record
Abstract
Chatbots are “computer agents that can interact with the user” in a way that feels like human-to- human conversation.1 While the use of chatbots for reference service in academic libraries is a topic of interest for both library professionals and researchers, little is known about how they are used in library reference service, especially in academic libraries in Canada. This article aims to fill this gap by conducting a web-based survey of 106 academic library websites in Canada and analyzing the prevalence and characteristics of chatbot and live chat services offered by these libraries. The authors found that only two libraries were using chatbots for reference service. For live chat services, the authors found that 78 libraries provided this service. The article discusses possible reasons for the low adoption of chatbots in academic libraries, such as accessibility, privacy, cost, and professional identity issues. The article also provides a case study of the authors’ institution, the University of Calgary, which integrated a chatbot service in 2021. The article concludes with suggestions for future research on chatbot use in libraries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".