Bibliographic record
Abstract
Over the past ten to fifteen years, health sciences universities have scrutinized, revised, and reformed their curricula in response to changes in accreditation, applicant pools, funding, licensing examinations, and recommendations made by the Association of American Medical Colleges (AAMC), the World Federation of Medical Education, and other organizations. Increased interest in program evaluation and student outcomes has emphasized the value of interactive small-group learning over didactic lectures. Recent curricular changes have afforded librarians unprecedented opportunities to participate in curriculum planning and to contribute to the success of student-centered learning. Health sciences librarians provide, organize, and support many of the resources, services, and facilities necessary for students to communicate, learn, research, manage biomedical information, teach, and succeed during their academic years and thrive later in professional practice. Problem-based learning (PBL) is an important component of recent medical education reform and poses special challenges for educators and librarians alike. This primer provides a rich context for understanding PBL by compiling and reprinting key articles from a variety of sources (Bulletin of the Medical Library Association, Academic Medicine, Postgraduate Medical Journal, Health Libraries Review, Journal of Dental Education, Journal of Nursing Education, Journal of Allied Health, etc.), supplemented by new material written by accomplished medical librarians such as Rankin, LaBeause, Dimitroff, Sayre, Fitzgerald, Eldredge, Leishman, and others. More than sixty contributors represent leading academic health sciences universities in North America (Mercer University School of Medicine, McMaster University, University of New Mexico, Tufts University, Dalhousie University, University of Nebraska Medical Center, and University of Toronto) with international perspectives from the Netherlands (University of Limburg at Maastricht), United Kingdom (University of Liverpool), and Sweden (Linkoeping University). Appropriately, this book is edited by the director of the Medical Library at Mercer University School of Medicine, an institution that introduced a full PBL curriculum when the medical school was established in 1982. The handbook is arranged into six major sections: “What is PBL?,” “Major PBL Issues,” “Measuring PBL Outcomes,” “Effects of PBL on Libraries: Reviews and Research,” “PBL and Libraries: New Roles and Program Opportunities,” and “Conclusion.” Librarians not yet involved in PBL will appreciate ideas and insights related to new roles and responsibilities such as serving as librarian-facilitators, providing train-the-trainer instruction for students, and participating in curriculum planning. History enthusiasts may be disappointed by the repetitive but cursory mention of Plato, Socrates, and landmark publications important to medical education reform (the Flexner report, GPEP report, and ACME-TRI report). The usefulness of this resource is enhanced by a four-page glossary, author-subject index, and six-page selected bibliography. Some libraries may wish to purchase several copies to distribute to colleagues on various curriculum committees.
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.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.092 | 0.074 |
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".