Leaning into sustainability at University of Alberta Libraries
Bibliographic record
Abstract
Purpose – The purpose of this paper is to present a case study that considers the links between cost avoidance, lean design, and sustainability in relation to two different library projects at University of Alberta Libraries (UAL) – the design of the Research and Collections Resource Facility and the development of new fee-based library services at UAL’s John W. Scott Health Sciences Library. Design/methodology/approach – This case study describes the analysis of each project’s workflows in relation to lean design in order to enhance processes and service delivery. Findings – Findings to date in both of these ongoing projects suggest that consideration of the lean philosophy has already led to process and service improvements. With regard to the new building design project, revised task design is already resulting in significant savings in staff time, and work space. And the staffing model for fee-based specialized services has already been redesigned, an alignment with lean principles. Research limitations/implications – While this paper does discuss and define lean design, it does not provide a comprehensive summary of research in this area. Originality/value – This paper highlights the value of lean design as a framework for designing, developing, and reviewing academic library buildings, services, processes, and workflows to ensure they are sustainable.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.011 | 0.009 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".