Accentuating Research Scholarship Through Innovative Student Opportunities: A Mentored Approach
Bibliographic record
Abstract
The _Journal for Advancing Sport Psychology in Research (JASPR)_ accentuates the development of research scholarship through highly immersive, mentored opportunities for students to first author rigorous student-led research and serve as gatekeepers (i.e., as peer-reviewers and editorial board members) of scientific knowledge through an innovative student-centered publishing platform. First-author publications are considered one of the foremost pinnacles of scientific achievement for research scholars; and, serving as peer reviewers and Editorial Board members of scientific journals are, respectively, considered two of the most valued professional service endeavors in the academic realm. _JASPR_’s student-centered operations are intended to enrich students’ knowledge of scientific publishing processes, develop and strengthen their scholarship skills, and bolster their abilities and motivation for navigating the complex academic publishing landscape. As the inaugural editors, in this paper, we: (a) call attention to opportunities in the research publishing landscape to involve students through mentored experiences, (b) broadly describe the role of mentorship in student scholarship, (c) introduce _ASPiRE_ which describes the journal’s mentoring activities and guides the immediate, short-term, and long-term student scholarship impacts in a logic model, and (d) provide an overview of opportunities for, and the benefits of, student involvement in the journal. Finally, we conclude with a call for student and faculty engagement in the journal.
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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 | 0.024 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.032 | 0.016 |
| Open science | 0.004 | 0.027 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".