Bibliographic record
Abstract
Objective – To determine if the implementation of well-advertised "librarian office hours" in a busy clinical department of a teaching hospital would increase utilization of library services. Setting – The open-concept office of the Department of Family and Community Medicine at the Toronto Western Hospital site of the University Health Network. Program – As of June 2004, a librarian provided monthly office hours during the lunch hour in the Department of Family and Community Medicine. Staff were encouraged to e-mail any specific issues or questions to the librarian in advance of consultation, if possible, but all consultations were otherwise provided on a first-come, first-served basis. Results – In the 7-month period since the librarian office hours were initiated, 21 separate training sessions or consultations were provided to this department. This constitutes 15 sessions more than the number of sessions provided to this group in the same 7-month period in the previous year. Concurrently, the number of literature search requests made by this department has doubled compared with the same 7-month period in the previous year. Conclusion – User-centered information services for primary care professionals need to be mindful of clients' information-seeking preferences and lack of time. While providing librarian visits to individual hospital departments may not be the best use of a librarian's limited time and resources, in the drive to meet the unique needs of general practice, such an approach may be an advantageous way of librarians meeting client needs in the context of their own environment. Further examination of the benefits of approaches similar to this concept, for both librarians and hospital staff, is warranted.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.006 |
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".