Bibliographic record
Abstract
Objective - In developing marketing strategies for the Business & Economics Library (BEL) at the University of Illinois at Urbana–Champaign (UIUC), a survey was designed to answer the following questions:
 
 • Should BEL develop marketing strategies differently for East Asian business students?
 • What services do graduate business students want to receive from BEL?
 • With whom should BEL partner to increase visibility at the College of 
 Business? 
 
 Marketing research techniques were used to gather evidence upon which BEL could construct appropriate marketing strategies.
 
 Methods - A questionnaire was used with graduate business students enrolled at UIUC. The survey consisted of four categories of questions: 1) demographics, 2) assessment of current library services, 3) desired library services, and 4) research behavior. The data were analyzed using descriptive statistics and hypothesis testing to answer the three research questions.
 
 Results - East Asian business students showed similar assessment of current services as non-East Asian international business students. Survey results also showed that graduate business students had low awareness of current library services. The Business Career Services Office was identified as a co-branding partner for BEL to increase its visibility.
 
 Conclusion - A marketing research approach was used to help BEL make important strategic decisions before launching marketing campaigns to increase visibility to graduate business students at UIUC. As a result of the survey, a deeper understanding of graduate business students’ expectations and assessment of library services was gained. Students’ perceptions became a foundation that helped shape marketing strategies for BEL to increase its visibility at the College of Business. Creating marketing strategies without concrete data and analysis is a risky endeavor that librarians, not just corporate marketers, should avoid.
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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 | 0.004 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.259 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".