Bibliographic record
Abstract
Whatever good intentions students may have to uphold academic integrity, they are subject to derailment due to contrary pressures leading to loss of integrity. A response focusing on breaches of academic integrity is mainly concerned with deterring students from committing breaches through different forms of punishment. The author describes this approach as a punishment-deterrence model and offers theoretical justification for why that approach is not conducive to the development of students’ academic integrity. The author then pursues an alternative approach, proceeding on the point that individual responsibility to uphold academic integrity is rooted in autonomous choice but emphasising that this point need not invoke an individualistic view. Social relations are key to the cultivation and exercise of integrity on the account the author presents. In this article, the author illuminates theoretical connections between autonomy and integrity, drawing on social connections as significant to each, with a main focus on establishing the theoretical importance of the connection between student academic integrity development and integrity support.
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
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 | 0.026 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.011 | 0.059 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.037 |
| 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, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".