Library Assessment and Quality Assurance - Creating a Staff-Driven and User-Focused Development Process
Bibliographic record
Abstract
Objective – Gothenburg University Library has implemented a process with the goal to combine quality assurance and strategic planning activities. The process has bottom-up and top-down features designed to generate strong staff-involvement and long-term strategic stability. Methods – In 2008 the library started implementing a system in which each library team should state a number of improvement activities for the upcoming year. In order to focus the efforts, the system has gradually been improved by closely coupling a number of assessment activities, such as surveys and statistics, and connecting the activities to the long-term strategic plan of the library. Results – The activities of the library are now more systematically guided by both library staff and users. The system has resulted in increased understanding within different staff groups of changing external and internal demands, as well as the need for continuous change to library activities. Conclusion – Library assessment and external intelligence are important for tracking and improving library activities. Quality assurance and strategic planning are intricate parts in sustainable development of better and more effective services. The process becomes more effective when staff-driven and built upon systematic knowledge of present activities and users.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
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 | 0.248 | 0.213 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.006 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.024 | 0.012 |
| Open science | 0.005 | 0.022 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.006 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".