Formality in Chat Reference: Perceptions of 17- to 25-Year-Old University Students
Bibliographic record
Abstract
Objective – To examine the ways in which the formality of language used by librarians affects 17- to 25-year-old university students’ perceptions of synchronous virtual reference interactions (chat reference), in particular, perceptions of answer accuracy, interpersonal connection, competency, professionalism, and overall satisfaction. Methods – This qualitative study used semi-structured interviews to examine the perceptions of participants. Participants reviewed and responded to two virtual reference transcripts, portraying a librarian and student asking a simple question. One transcript portrayed a librarian using traditional, formal language while the other portrayed a librarian using informal language. Five 17- to 25-year-old university students were interviewed. Data were analyzed using a phenomenological, qualitative approach to discover common themes. Results – Analysis suggests that participants perceived the formal librarian as being “robotic” and impersonal while the informal librarian was thought to be more invested in the reference interaction. Several participants viewed the formal librarian as more competent and trustworthy and questioned the effort put forth by the informal librarian, who was perceived as young and inexperienced. Participants’ perceptions of professionalism were based on expectations of social distance and formality. Satisfaction was based on content and relational factors. Several participants preferred the formal interaction based on perceptions of competency, while others preferred the informal librarian due to perceived interpersonal connection. Conclusion – Formality plays a key role in altering the perceptions of 17- to 25-year-olds when viewing virtual reference interaction transcripts. Both language styles had advantages and disadvantages, suggesting that librarians should become cognizant of manipulating their language to encourage user satisfaction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".