Bibliographic record
Abstract
The Japan Aerospace Exploration Agency (JAXA) is among the six largest national space agencies in the world, along with China's CNSA, US's NASA, and Russia's Roscosmos. JAXA's budget is more than $1 billion USD—bigger than France or Germany individually, and more than that of Italy, India, Canada, and the UK combined. And yet, Japan's significant contributions have largely been absent in the history of space exploration, and space exploration largely absent in the history of technology in Japan. The Islands and the Stars corrects this conspicuous oversight. Through meticulous archival research in Japanese and anglophone archives, Subodhana Wijeyeratne examines the history of Japan's space exploration efforts over nearly a century. Wijeyeratne traces the evolution of Japan's space program from its early origins in the 1920s, through the postwar period of rapid technological innovation, to the consolidation of its various institutional elements into JAXA in 2003. He situates Japan's space programs within the broader history of the country's postwar recovery, economic growth, and cultural identity, while also considering their place within global trends in space exploration. Through this narrative, Wijeyeratne not only illuminates Japan's centrality to the global history of science and technology, but also offers insights into the future of global space exploration, emphasizing the importance of diverse voices and perspectives in the quest to understand our place in the cosmos.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".