Reimagining Research Services as Part of Major Academic Library Renovations or Other Changes: A Tale of Two Research Departments (University of Central Florida and Florida Gulf Coast University)
Bibliographic record
Abstract
Two academic library research service managers discuss changes and innovations that they have coordinated in their respective libraries: University of Central Florida serving 60,000+ students (http:// library .ucf .edu /21st/) and Florida Gulf Coast University serving 15,000+ students (http:// library .fgcu .edu /admin /renewal .html) due to major building renovations or other changes that their respective libraries are conducting. These changes and innovations include significantly downsizing print reference and other collections, relocating service points, reconfiguring public services, rethinking staffing patterns, adjusting subject librarian face-to-face activities, stepping up online services, communicating with stakeholders, and keeping students and faculty in the loop so that their voices are heard and their needs met.
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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 | 0.044 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.009 |
| Scholarly communication | 0.017 | 0.015 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".