Bibliographic record
Abstract
BACKGROUND: The number of public health degrees and programmes is growing rapidly. This means that a diverse and multidisciplinary group of students are in need of expert library services to navigate the complicated world of public health information. OBJECTIVE: To better understand the information needs of public health students, a group that has not previously been studied in the information needs literature. METHODS: An online survey. RESULTS: Of the 153 students, 38 responded (25% response rate). Their responses indicated a strong need for more tailored library instruction sessions at the point of need as opposed to general stand-alone sessions offered at the beginning of a term. It was also found that many students were unaware of public health specific resources available that could greatly aid them in their information needs. Suggestions were made on how to improve the library subject guide, specifically in the areas of more instructions related to locating hard to find resources (e.g. statistics, grey literature), and direct linking to resources (e.g. databases and relevant articles). CONCLUSION: The information needs of public health students are diverse and complex. It is imperative that the library has a solid understanding of their needs and is able to offer them targeted and relevant library services.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".