Bibliographic record
Abstract
Abstract War and Peace in Outer Space examines the legal, policy, and ethical issues animating current concerns regarding the growing weaponization of outer space and the potential for a space-based conflict in the very near future. A collection of diverse voices rather than the product of a single scholarly mind, it builds upon a conference that was held in Philadelphia in April 2018, hosted by the Center for Ethics and the Rule of Law, at the University of Pennsylvania Law School, and designed by co-editor Cassandra Steer. The conference was an exceptionally high-level invitation-only roundtable for the duration of two days, attended by approximately thirty experts on space warfare from Canada, Europe, and the United States. In addition to calling attention to likely current and future threats to national and global security stemming from the use and misuse of the space environment, attendees suggested measures for ameliorating the risk of conflict in space, including international negotiation, transparency, and reporting on the use of space-based assets, and the establishment of clear rules, backed up by sanction regimes, against hostile actions that threaten the peaceful use of space by all nations.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.478 | 0.290 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".