Differences in Faculty Approaches to Plagiarism Deterrence are an Opportunity for Increased Collaboration in Information Literacy Instruction
Bibliographic record
Abstract
A Review of:
 Michalak, R., Rysavy, M., Hunt, K., Worden, J., & Smith, B. (2018). Faculty perceptions of plagiarism: Insight for librarians’ information literacy programs. College and Research Libraries, 79(6), 747-767. https://doi.org/10.5860/crl.79.6.747 
 Abstract
 Objective – To learn how faculty members define plagiarism and what actions (if any) they are taking in their classes to educate students about plagiarism.
 Design – Online survey.
 Setting – A small private college in the Northeastern United States of America.
 Subjects – A total of 79 full-time and adjunct faculty members in arts and business.
 Methods – Participants completed an online survey, modified from a survey in The Plagiarism Handbook, in which they provided their definition of plagiarism. They then answered yes/no questions regarding their knowledge levels and methods of plagiarism instruction used in class. The authors collected data on the faculty members’ age, discipline, years of experience, and their status as either adjunct or full-time faculty. After analyzing the results independently, the authors later collaborated to discuss codes and identify clear themes in the list of definitions.
 Main Results – An analysis of faculty members’ plagiarism definitions determined that most define plagiarism in a way that roughly aligns with the university’s definition, but identified inconsistencies regarding severity, student knowledge, the role of intent, and the necessity of a source attribution when determining what constitutes plagiarism. The themes in their responses clearly illustrate the major differences in approaches to plagiarism.
 The authors also found that while 87% of respondents reported discussing plagiarism in their classes, they usually did so only “a little” or “a moderate amount.” Furthermore, just over 53% of respondents did not provide their students with materials on plagiarism, though 55% reported including a definition of plagiarism in their course syllabi. Researchers also asked whether or not faculty members had invited a librarian to speak to their class about plagiarism, to which 74% of faculty members responded no.
 Conclusion – This study suggested that librarians should consider differing perspectives on plagiarism when collaborating with faculty members and that librarian-faculty collaboration on information literacy instruction can help to mitigate the effects of inconsistent practices regarding plagiarism. The study’s authors are integrating their research findings into anti-plagiarism training modules for students at the institution where this study was conducted. Future studies based on this research are planned to further explore the intersections of plagiarism and information literacy.
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
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 | Research integrity Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | medium |
| gpt | Research integrity Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.303 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".