“Discovering” what's changed: a revisit of the OPACs of 260 academic libraries
Bibliographic record
Abstract
Purpose This paper aims to determine the current usage of next generation online public access catalogs (OPACs) and discovery tools in academic libraries in the USA and Canada. Design/methodology/approach Using the same random sample of 260 colleges and universities in the USA and Canada from their original study, the authors revisited each institution's library web page to ascertain whether the OPAC interface(s) offered were the same or different than in their initial data collection. Data was collected and analyzed in October and November 2011. Findings Discovery tool use has practically doubled in the last two years, from 16 percent to 29 percent. A total of 96 percent of academic libraries using discovery tools still provide access to their legacy catalog. The percentage of institutions using ILS OPACs with faceted navigation has increased from 2 percent to 4 percent. Combining the use of discovery tools and faceted OPACs, at least 33 percent of academic libraries are now using a faceted interface. Discovery tools that aim to be the “single point of entry for all library resources” are the most recently popular. Research limitations/implications About 16 percent of the institutions (n=43) in the sample either did not have web sites or did not provide access to their online catalogs. Thus, some data might be underreported. Practical implications The findings identify trends that may inform academic libraries in the quest to providing next generation interfaces to their varied resources. Originality/value This study gives a timely update of next generation catalog (NGC) and discovery tool usage in academic libraries in the USA and Canada.
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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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.040 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".