Image-Seeking Preferences Among Undergraduate Novice Researchers
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
Objective – This study investigated the image-seeking preferences of university freshmen to gain a better understanding of how they search for pictures for assignments.
 
 Methods – A survey was emailed to a random sample of 1,000 freshmen enrolled at Oregon State University in the fall of 2009. A total of 63 surveys were returned.
 
 Results – The majority of students indicated they would use Google to find a picture. Nineteen respondents said they would use a library, librarians, and/or archives.
 
 Conclusions – The results indicate the majority of students in our study would use Google to find an image for coursework purposes; yet the students who suggested they would use Google did not mention evaluating the images they might find or have concerns about copyright issues. Undergraduate students would benefit from having visual literacy integrated into standard information literacy instruction to help them locate, evaluate, and legally use the images they find online. In addition, libraries, librarians, archivists, and library computer programmers should work to raise the rankings of library digital photo collections in online search engines like Google.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.280 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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