Nutrition, Food Science, and Dietetics Faculty Have Information Needs Similar to Basic and Medical Sciences Faculty – Online Access to Electronic Journals, PubMed/Medline, and Google
Bibliographic record
Abstract
Objective – To determine the information needs of nutrition, food science, and dietetics faculty members by specifically examining how they locate and access information sources and which scholarly journals are consulted for teaching, research, and current awareness; and identifying any perceived information service needs (e.g., training). Design – Online survey questionnaire. Setting – Four senior colleges within the City University of New York (CUNY) system. Subjects – Nutrition, food science, and dietetics faculty members. Methods – Using institutional websites and the assistance of relevant affiliated librarians, 29 full-time and adjunct nutrition, food science, and dietetics faculty members were identified at Queens College, Brooklyn College, Hunter College, and Lehman College (all part of the CUNY system). A survey was emailed in June and July 2007 and had 14 (48.4%) responses. The study was temporarily halted in late 2007. When resumed in January 2009, the survey was re-sent to the initial non-respondents; five additional responses were received for a final 65.5% (n=19) response rate. Main Results – The majority of respondents held a PhD in their field of study (63.1%), were full-time faculty (no percentage given), and female (89.5%). Information sources were ranked for usage by respondents, with scholarly journals unsurprisingly ranked highly (100%), followed by conference and seminar proceedings (78.9%), search engines (73.6%), government sources (68.4%), and information from professional organizations (68.4%). Respondents ranked the top ten journals they used for current awareness and for research and teaching purposes. Perhaps due to a lack of distinction by faculty in terms of what they use journals for, the two journal lists differ by only two titles. The majority browse e-journals (55.6%) rather than print, obtain access to e-journals through home or work computers (23.6%), and obtain access to print through personal collections (42.1%). Databases were cited as the most effective way to locate relevant information (63.1%); PubMed was the most heavily used database (73.7%), although Medline (via EBSCO), Science Direct, and Academic Search Premier were also used. Respondents were asked how they preferred to obtain online research skills (e.g., on their own, via a colleague, via a librarian, or in some other way). The linked data does not answer this question, however, and instead supplies figures on what types of sessions respondents had attended in the past (44.4% attended library instruction sessions, while others were self-taught, consulted colleagues, attended seminars, or obtained skills through their PhD research). Conclusion – Strong public interest in nutritional issues is a growing trend in the Western world. For those faculty members and scholars researching and teaching on nutrition and related areas, more work on their information needs is required. This study begins to address that gap and found that nutrition, food science, and dietetics faculty share strong similarities with researchers in medicine and the other basic sciences with regard to information needs and behaviours. The focus is on electronic journals, PubMed/Medline, and online access to resources. Important insights include the fact that print journals are still in modest use, researchers use grey literature (e.g., government sources) and other non-traditional formats (e.g., conference proceedings and electronic mail lists) as information sources, and training sessions need to be offered in a variety of formats in order to address individual preferences.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.043 | 0.005 |
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".