Search Success at the University of Manitoba Libraries Pre- and Post-Summon Implementation
Bibliographic record
Abstract
The University of Manitoba Libraries (UML) hired an external company to perform usability testing on its website in 2008 and 2009. A component of the website testing required test participants to find particular books and articles and to identify materials on a particular specific topic using the UML’s search tools. The need for a resource discovery tool was made clear when participants were not generally successful in completing these tasks. The UML released Request for Proposals (RFP) for a resource discovery tool in 2010 and shortly afterward acquired Summon™1 as the successful tool. Usability testing was performed on the Summon™ resource discovery tool while it was still in beta development at UML to see if there was an improvement in search success for students. The results of the two usability studies are described in this chapter, with an emphasis on the Summon™ usability testing and suggestions for further research.
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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 | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.007 |
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".