Information Seeking Behaviors, Attitudes, and Choices of Academic Chemists
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Chemists in academic institutions utilize a variety of resources and strategies to remain current and to track scholarly information, patents, and news. To explore how chemists in academic institutions remain current, librarians at four Canadian university institutions surveyed 231 and interviewed 14 chemistry faculty, staff, and graduate students on their information seeking behaviors and attitudes. According to survey results, a minority of chemists (13.9 percent) acknowledged that they were successfully keeping up to date, while 50.6 percent indicated that they were somewhat successful. However, a significant number of chemists (35.5 percent) indicated that they were unsuccessful and could do better in remaining current with information. Investigators analyzing focus group data identified three emergent themes related to remaining current: (1) there is “too much information – and not enough time.” No single information seeking strategy works; (2) “patents are important – but \nmessy.” Chemists find themselves largely suspicious about the value and credibility of patents; and (3) chemists “could do \nbetter” in keeping up to date with new and emerging technologies. Chemists continue to be open to new tools and resources \nyet readily acknowledge that they are too often not sure which information seeking behaviors, resources, or strategies work \nbest. This study helps to shed light on opportunities to identify and meet chemists’ evolving information needs.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.053 | 0.177 |
| Science and technology studies | 0.001 | 0.010 |
| Scholarly communication | 0.001 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it