Personality and Employees’ Information Security Behavior among Generational Cohorts
Bibliographic record
Abstract
The Big Five Factors Model (FFM) of personality traits theory was tested for its ability to explain employee information security behavior (EISB), when age, measured by generational cohort (GCOHORT), moderated the relationship between the independent variables (IVs) extraversion, agreeableness, conscientiousness, emotional stability, intellect (EACESI) and the dependent variable (DV), employees’ information security behavior (EISB) which is measured by file protection behavior (FPB). Three age groups defined GCOHORT: 52–70 years old (1946–1964, Baby Boomers), 36–51 yrs old (1965–1980, Generation X), and 18– 35 yrs. Old (1981–1998, Millennial). Results of hierarchical multiple regressions analyses revealed statistically significant relationships between overall personality traits, four individual factors of personality traits, and the DV (p < .05). However, contrary to expectations, GCOHORT did not moderate the relationship between any of the main IVs and the DV (p > .05). Recommendations for future research are offered.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".