Undergraduate research in the public domain: the evaluation of non‐academic sources online
Bibliographic record
Abstract
Purpose This paper seeks to suggest that criteria commonly used to teach undergraduates to evaluate online resources are inadequate when dealing with non‐academic items in the public domain. It aims to argue that these resources should not be ignored by librarians or undergraduates, but that they must still be evaluated. An alternative method of evaluation, based on the concepts of comparison, corroboration, motivation and purpose is to be proposed. Design/methodology/approach Inadequacies of current evaluative standards are revealed, specifically in relation to the current context of how and where undergraduates conduct research. Drawing on Meola's contextual framework for evaluation, as well as the thoughts of Metzger, ways to handle the evaluation of non‐academic resources online emerge. Findings Librarians must consider the place of non‐academic public domain items in current undergraduate research projects, and the challenges these items pose to common guidelines for the evaluation of sources. Evaluation methods must be rethought and based on a more context‐specific approach in order to be relevant when working with non‐academic resources online. Originality/value Librarians who focus mainly on the “peer‐reviewed” designation or other standard evaluative criteria to help students determine what an appropriate research resource is, and who are unsure of how to guide students in their use of non‐academic public domain items, will find here suggestions to guide their thinking and inform their practices.
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.
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 | 0.202 | 0.344 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".