Reorganizing a Technical Services Division Using Collaborative Evidence Based Information Practice at Auraria Library
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
Objective - The objective of this article is to demonstrate the efficacy of collaborative Evidence Based Information Practice (EBIP). 
 
 Methods - Application of theoretical frameworks of shared leadership, appreciative inquiry, and knowledge creation to propose an organisational effectiveness model.
 
 Results - The Auraria Library case study demonstrates the introduction of a collaborative EBIP culture – reorganizing personnel, reassigning responsibilities, and measuring outcomes – successfully within a technical services division. By doing so, participants are encouraged and empowered to identify problems and create solutions amidst a dynamically changing electronic resources environment. 
 
 Conclusions - Auraria Library’s technical services department created a collaborative EBIP environment by flattening workplace hierarchies, distributing problem solving and encouraging reflective dialogue. Embracing the collective knowledge and experiences of Technical Services staff members enables them to be valued and respected leaders and followers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.736 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it