Black, White, and Grey: (Re)Constructing the One-Size-Fits-All Approach to Plagiarism
Bibliographic record
Abstract
The purpose of this qualitative study is to explore how plagiarism is discursively constructed and taken up within a North American university and what challenges result from its multiple interpretations.Rhetorical move analysis (Swales, 1990) is used to investigate how plagiarism is constructed in the university's Academic Integrity Policy (AIP) and how it is (re)constructed in course outlines from the departments of Education Research and Life Sciences.The study further uses concepts of intertextuality and uptake to investigate how professors and students from different disciplinary discourse communities interpret the institutional definition of plagiarism by either adopting it in its entirety or by adapting it.Move analysis indicates that the AIP constructs a universal interpretation of plagiarism while the analysis of interviews with four professors points to a three-to-one split: three professors took up the AIP by reinterpreting it and implementing their own way of dealing with instances of plagiarism and one took up the AIP in expected ways.Students, however, seem to understand plagiarism, partially, in ways similar to the AIP and, partially, similar to professors.The findings of the study suggest that the "one size" institutional AIP may not address possible types and interpretations of plagiarism.
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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 | Research integrity Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | Research integrity Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.051 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.028 | 0.049 |
| Scholarly communication | 0.012 | 0.018 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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, 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".