The Importance of Social Mechanisms in the Commission of or Resistance to Group Fraud: A Field Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We analyze 19 stories from individuals who committed group fraud and 19 from those who resisted pressure to commit group fraud. Our goal is to better understand the control mechanisms that helped push people toward or against group fraud. Our theoretical lens highlights the implications of the social nature of “group” fraud and classifies the mechanisms we examine into social and administrative mechanisms. Social mechanisms are based on the influence of others (e.g., culture, mentorship) while administrative mechanisms are based on rules and policies (e.g., reward systems). We find that social mechanisms are significantly more influential than administrative mechanisms in pushing individuals toward the commission of and resistance to group fraud. Leveraging Qualitative Comparative Analysis, we also identify combinations of control mechanisms that commonly lead to the commission of and resistance to group fraud. Our field study enriches group fraud literature and identifies control mechanisms in which practitioners should invest.
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.
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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it