A review and analysis of deterrence theory in the IS security literature: making sense of the disparate findings
Why this work is in the frame
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Bibliographic record
Abstract
Deterrence theory is one of the most widely applied theories in information systems (IS) security research, particularly within behavioral IS security studies. Based on the rational choice view of human behavior, the theory predicts that illicit behavior can be controlled by the threat of sanctions that are certain, severe, and swift. IS scholars have used deterrence theory to predict user behaviors that are either supportive or disruptive of IS security, and other IS security-related outcome variables. A review of this literature suggests an uneven and often contradictory picture regarding the influence of sanctions and deterrence theory in general in the IS security context. In this paper, we set out to make sense of the discrepant findings in the IS deterrence literature by drawing upon the more mature body of deterrence literature that spans multiple disciplines. In doing so, we speculate that a set of contingency variables and methodological and theoretical issues can shed light on the inconsistent findings and inform future research in this area. The review and analysis presented in this paper facilitates a deeper understanding of deterrence theory in the IS security domain, which can assist in cumulative theory-building efforts and advance security management strategies rooted in deterrence principles.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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