Bibliographic record
Abstract
As Western post-secondary institutions strive to adequately prepare undergraduate students for an ever-changing world, increased interest and investment has been directed towards the undergraduate learning experience. Listed as a high-impact practice (Kuh 10), undergraduate research, in particular, has been increasingly implemented and expanded in a number of institutions over the past several decades, as shown by the growth of the Council on Undergraduate Research (CUR n. pag.). With the rise of undergraduate research culture, the undergraduate research journal (URJ) has emerged. URJs run within a university provide students with the opportunity to enhance their education through exposure to scholarly publishing, develop their research and communication skills, view themselves as content creators, produce higher quality work, and improve their graduate school applications or resumes by building essential skills for the changing job market. Despite the variability present in URJ formats, I have defined two broad categories which URJs fall into. Distinguished as “showcase” and “selective” journals, the two types are differentiated by the implementation of a peer-review process with “showcase” journals publishing papers that have not undergone peer-review and “selective” journals qualifying as scholarly publications. With the intent of providing the maximum benefit to the greatest number of students, a “showcase” journal, without the rigours of peer-review, may appear to be the best fit for achieving this goal as it has the potential to see more student papers published. However, the “selective” showcase journal provides the most cumulative benefits for the student, the institution, and the wider academic community. This is due to experiencing the submission process, which provides students with feedback from reviewers; the prestige of publishing in or housing a high-quality journal; and, growing a discipline’s body of knowledge. While providing any type of publishing platform for undergraduate student work will benefit students, institutions may wish to consider the additional worth of “selective” journals when developing an undergraduate research journal program.
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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 | 0.018 | 0.091 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.018 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.013 |
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".