Librarian and Researcher Assessments of Search Result Relevance: How Well Do They Align?
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
Conducting comprehensive but efficient literature searches for complex evidence syntheses involves selecting databases that will retrieve the greatest number of relevant results on the question. Lack of a comprehensive single database on allied health educational topics challenges those seeking such literature. In this study, six participants contributed research questions on instructional methods and materials for allied health patients, caregivers, and future health professionals. Two health sciences librarians created search strategies for these questions and searched eleven databases. Both the librarians and the six participants evaluated the search results using a rubric based on PICO to assess extent of alignment between the librarians' and requestors' relevance judgments. Intervention, Outcome, and Assessment Method constituted the most frequent bases for assessments of relevance by both librarians and participants. The librarians were more restrictive in all of their assessments except in a preliminary search yielding twelve citations without abstracts. The study's results could be used to identify effective techniques for reference interviewing, selecting databases, and weeding search results.
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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it