Toward Understanding Distributed Cognition in IT Security Management: The Role of Cues and Norms
Bibliographic record
Abstract
Information technology security management (ITSM) entails significant challenges, including the distribution of tasks and stakeholders across the organization, the need for security practitioners to cooperate with others, and technological complexity. We investigate the organizational processes in ITSM using qualitative analysis of interviews with ITSM practitioners. To account for the distributed nature of ITSM, we utilized and extended a distributed cognition framework that includes as key aspects the themes of cues and norms. We show how ITSM challenges foster under-use of cues and norms, which comprises a type of risk that may result in outcomes that are adverse to the organization's interests. Throughout, we use scenarios told by our participants to illustrate the various concepts related to cues and norms as well as ITSM breakdowns.
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How this classification was reachedexpand
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 | 0.018 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.038 |
| Scholarly communication | 0.013 | 0.026 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".