Out with the Old, In with the New: Examining National Cybersecurity Strategy Changes over Time
Bibliographic record
Abstract
The development and implementation of a national cybersecurity strategy (NCS) is becoming increasingly common for countries around the world that seek to define an approach for addressing their cybersecurity risks. Although past research has sought to classify the individual characteristics contained within an NCS, it remains unclear how the core content within a strategy evolves over time in the face of new cyber threats and fluctuating priorities. By better understanding such changes (and their underlying drivers), policy makers can be increasingly attuned to essential NCS updates and citizens can more readily evaluate the adequacy of their country’s plans. This study examines multiple NCS versions in Canada, the United Kingdom, and Australia using a qualitative, content analysis approach. Our results point to four core themes that characterize NCS stability and change over time. Based on our observations, we articulate several theoretical propositions and outline a plan for future research.
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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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.014 | 0.002 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".