Using Academic Librarians and the Academic Library: Survey Results from Mathematics Faculty in United States and Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Despite our diligent outreach and relationship-building efforts, certain groups of faculty within STEM disciplines remain hesitant to engage with academic librarians and utilize library resources. This challenge raises a critical question: How can librarians effectively support a department when faculty members are unresponsive? <br> Our research team, composed of three frustrated mathematics librarians and one mathematics faculty member, recognized the need for a fresh approach. Mathematics, a department known for its independence, has received limited attention in scholarly Library and Information Science (LIS) literature. To address this gap, we embarked on a project to understand mathematics faculty’s perspectives and needs regarding library services. Our research aimed to explore mathematics faculty’s use of library resources and their perceptions of academic librarians. We sought insights into their attitudes, which would inform strategies for more effective collaboration. <br> To achieve this, our team designed a concise 10-minute survey for mathematics faculty across higher education institutions in the United States and Canada. We received 189 responses, providing valuable data for analysis. In this presentation, we will share preliminary findings from our survey conducted in the fall of 2023. The survey included both qualitative (free-text responses) and quantitative (Likert scales and multiple choice) questions. We will also discuss outreach and engagement strategies informed by the survey results, along with examples of faculty perspectives. Additionally, we aim to engage attendees in a discussion to hear their solutions and frustrations in working with less responsive disciplines, such as Mathematics. We believe that many colleagues will have valuable experiences and ideas to contribute, which will help us all collaborate more effectively with some of our more challenging departments. In summary, our project bridges the gap between mathematics faculty and academic librarians by aligning services with faculty needs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it