Effect of Undergraduate Research Output on Faculty Scholarly Research Impact
Bibliographic record
Abstract
Abstract Objective – In the context of the ongoing discourse about the role of Institutional Repositories (IRs), the objective of the study is to investigate if there is any evidence of a relation between undergraduate student activity in an IR and the impact of faculty research. Methods – The data used for the study is representative of six academic departments of the College of Science and Mathematics (CSM) at California Polytechnic State University (Cal Poly). Digital Commons@Cal Poly (DC) is the IR supported by the library. Regression analysis was used to investigate the interdependence between faculty research impact (dependent variable) and undergraduate student repository activity (independent variable). For each department, faculty research impact was quantified as a measure of the citation counts for all faculty publications indexed in Web of Science (WoS) between January 2008 and May 2017. Student repository activity was quantified for each department in two ways: (1) total number of student projects deposited in DC since 2008 (Sp) and (2) total number of student project downloads from DC (Sd). The dependent variable was regressed against each of the two elements of student repository activity (Sp and Sd), and the resulting statistics (sample correlation coefficients, coefficients of determination, and linear regression coefficients) were calculated and checked for statistical significance. Results – The statistical analysis showed that both components of student repository activity are positively and significantly correlated with the impact of faculty research quantified by a measure of the citation counts. It was also found that faculty repository activity, although positively correlated with faculty research impact, has no significant effect on the correlation between student repository activity and faculty research impact. Conclusion – The analysis considers two distinct groups of publications: one group of student publications (senior projects) from six academic departments, which are deposited in an open repository (DC), and one group of publications (not necessarily represented in DC) of faculty affiliated with the same six departments and whose citation impact is believed to be affected by the first group. The statistical correlation between student repository activity and faculty research impact can be seen as an indication that an active, open IR centered on collecting, preserving, and making discoverable student research output has a positive impact on faculty’s research impact. More research that includes additional factors and uses a larger data set is necessary to arrive at a definitive conclusion.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchBibliometrics Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Metaresearch Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
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 | 0.020 | 0.203 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".