Bibliographic record
Abstract
Cyber-Diplomacy: Managing Foreign Policy in the Twenty-First Century, Evan H. Potter, ed., Montreal & Kingston: McGill-Queen's University Press, 2002, xii, 208. We are repeatedly told that we live in a revolutionary age, a time in which dramatic new developments in information and communication technologies (ICTs) will fundamentally transform the ways in which we live and work. Even the collapse of the dot.com bubble in 2000 has not much dampened the spirits of the techno-utopians. Given these often-exaggerated claims, I approached Cyber-Diplomacy with some trepidation, as the editor cites Marshall McLuhan's ‘global village’ in the first line of his introduction, and speaks of an information revolution in his second paragraph. However, as I pressed on in the text I was very pleasantly surprised to find that the editor and authors of this short volume are well aware of the dangers of overstatement in relation to ICTs, and work very hard throughout to avoid techno-utopianism. Instead, the authors attempt to take a fairly sober look at “how diplomacy is adapting to the new global information order” (7).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".