Building a Regional Library-Led Case Competition: Reflections from Librarians and Vendor Partners
Bibliographic record
Abstract
Libraries are increasingly involved in supporting and facilitating case competitions, leading to competitions that emphasize decision-making and understanding of a larger ecosystem of information. This paper examines existing literature on the topics of librarian support for case competitions, the growing trend of library-led case competitions, and the expanded role of libraries in support of entrepreneurs, students, and faculty in entrepreneurial programs. The conversation is expanded through a discussion of the Midwest Entrepreneurship Case Competition (MECC), a library-led case competition that prioritized the participation of undergraduate students and grew from a local to a regional event. Vendor engagement, case development, competition format, timeline, and execution are shared and analyzed. Reflections from three stakeholders, including a first-time case competition planner, case competition judge, and vendor partner, enumerate MECC’s benefits to librarianship and student learning, approaches to information literacy, and opportunities for hands-on engagement in the development and marketing of tools. This research demonstrates the value of library-led case competitions as interventions for building transferable business information literacy skills and mechanisms for shaping and furthering collaboration among libraries, librarians, students, and vendors.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".