Electronic Resource Availability Studies: An Effective Way to Discover Access Errors
Bibliographic record
Abstract
Abstract Objective – The availability study is a systems research method that has recently been used to test whether library users can access electronic resources. This study evaluates the availability study’s effectiveness as a troubleshooting tool by comparing the results of two availability studies conducted at the same library before and after fixing access problems identified by the initial study. Methods – The researcher developed a six-category conceptual model of the causes of electronic resource errors, modified Nisonger’s e-resource availability method to more closely approximate student information-seeking behaviour, and conducted an availability study at the University of Redlands Armacost Library to estimate how many resources suffered from errors. After conducting troubleshooting over a period of several months, he replicated the study and found increased overall availability and fewer incidences of most error categories. He used Z tests for the difference of two proportions to determine whether the changes were statistically significant. Results – The 62.5% availability rate in the first study increased after troubleshooting to 86.5% in the second study. Z tests showed that troubleshooting had produced statistically significant improvements in overall availability, in the number of items that could be downloaded from the library’s online collection or requested through interlibrary loan (ILL), and in three of six error categories (proxy, target database and ILL). Conclusion – Availability studies can contribute to successful troubleshooting initiatives by making librarians aware of technical problems that might otherwise go unreported. Problems uncovered by an availability study can be resolved through collaboration between librarians and systems vendors, though the present study did not demonstrate equally significant improvements across all types of errors. This study offers guidance to librarians seeking to focus troubleshooting efforts where they will have the greatest impact in improving access to full-text. It also advances the availability research method and is the first attempt to quantify its effectiveness as a troubleshooting tool.
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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 | 0.038 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".