The Health Association Libraries Section survey: finding clues to changing roles
Bibliographic record
Abstract
The frequent discourse and debate on the roles of librarians generally includes a consensus about the broad position characteristics 1–3 that former Journal of the Medical Library Association (JMLA) Editor T. Scott Plutchak, AHIP, FMLA, summarizes well: “We connect people to knowledge. We bring people together with the intellectual content of the past and present so that new knowledge can be created. We provide the ways and means for people to find entertainment and solace and enlightenment and joy and delight in the intellectual, scientific and creative work of other people” 3. Health association libraries, a unique blend of medical and special libraries, have been surveyed periodically since 1955 (Appendix A, online only). The Health Association Libraries Section (HALS) of the Medical Library Association and its predecessors surveyed health association libraries in 1980, 1996, and 2003 on the status of these libraries and their services (Appendix B, online only). The 1980 survey focused on basic library data about clientele, collections, and staff. Surveys since then have included questions on services, funding, and stability. The surveys captured reasons for library closures, including changes in association leadership, budgets, space, objectives, and staffing. The surveys also captured reasons for success, including the ability of librarians to adapt their services to the needs and objectives of their parent organizations. The data collected from the most recent survey in 2011 helps to illuminate the new and changing roles of health association librarians and provide clues on how health association librarians can position themselves for the future.
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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 | 0.012 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".