When the generation gap collides with military structure: The case of the Norwegian cyber officers
Bibliographic record
Abstract
As the military integrates into its structures, gradually more nations are recruiting and educating personnel to serve as cyber officers. Tech-savvy men and women from ‘Generation Y’ grew up in the post-modern era, recognized not only by its individualism and erosion of overarching, coherent maxims, but also by the fact that technology is taken for granted. Thus, in the situation of the officer a particular generation gap occurs, one in which the characteristics of postmodernity, military command structures and the inter-disciplinarity of pull in conflicting directions. This friction creates a peculiar situation as technology and contribute to sharpen the generation gap that necessarily exists between the young generation of officers, and their superiors in the military. I explore this quandary through an examination of officers’ testimonies. In particular, I focus on the officers’ conceptualization of “cyber” and how this resonates with that of their superiors’. The data is ethnographic, based on interviews with officer students at the Norwegian Defence Cyber Academy.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.017 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".