The effect of spelling and retrieval system familiarity on search behavior in online public access catalogs: A mixed methods study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Although technology can often correct spelling errors, the complex tasks of information searching and retrieval in an online public access catalog (OPAC) are made more difficult by these errors in users' input and bibliographic records. This study examines the search behaviors of 38 university students, divided into groups with either easy‐to‐spell or difficult‐to‐spell search terms, who were asked to find items in the OPAC with these search terms. Search behaviors and strategy use in the OPAC and on the World Wide Web (WWW) were examined. In general, students used familiar Web resources to check their spelling or discover more about the assigned topic. Students with difficult‐to‐spell search terms checked spelling more often, changed search strategies to look for the general topic and had fewer successful searches. Students unable to find the correct spelling of a search term were unable to complete their search. Students tended to search the OPAC as they would search a search engine, with few search terms or complex search strategies. The results of this study have implications for spell checking, user‐focused OPAC design, and cataloging. Students' search behaviors are discussed by expanding Thatcher's (2006) Information‐Seeking Process and Tactics for the WWW model to include OPACs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it