Undergraduate Students’ Library Interactions: Does Race Shape How Students Experience Library Help?
Bibliographic record
Abstract
Objective – The goal of this study was to examine whether an undergraduate student's race influences their interactions and perceived quality of experiences with librarians/library staff and student employees. Methods – The study consisted of a survey distributed by email to undergraduate students at a medium size public university located in North Central Massachusetts. Students answered questions about the frequency of their interactions with librarians and student employees, whether they felt respected during the interactions, whether their information needs were met, and whether the interactions increased their feelings of belonging at the university. Data analysis on the 366 students who completed the survey was conducted in SPSS using Fisher’s exact test. Results – Findings revealed that Black students reported more frequent interactions with librarians/library staff and student employees than Latina/o/e and White students did. The difference across races regarding the frequency of interactions with librarians/library staff and student employees was statistically significant. Although Black students also reported higher levels of agreement for feeling respected, having their information needs met, and feelings of belonging than their counterparts, the differences among races were not statistically significant. Black, Latina/o/e, and White students felt respected, had their information needs met, and felt a sense of belonging regardless of whom they interacted with. Further, preferences for whom students interacted with depended on the type of information needed. Students sought librarians for research help and student employees for logistical support. Conclusion – To improve the undergraduate student library experience, the authors discuss how to create a more accessible and inclusive library environment by leveraging student employees for peer mentoring, enhancing faculty collaboration to integrate library resources into coursework, and providing professional development for library staff to foster a welcoming atmosphere.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".