Bibliographic record
Abstract
We discuss how visions for the futures of humanity in space and SETI are intertwined, and are shaped by prior work in the fields and by science fiction. This appears in the language used in the fields, and in the sometimes implicit assumptions made in discussions of them. We give examples from articulations of the so-called Fermi Paradox, discussions of the settlement of the Solar System (in the near future) and the Galaxy (in the far future), and METI. We argue that science fiction, especially the campy variety, is a significant contributor to the ‘giggle factor’ that hinders serious discussion and funding for SETI and Solar System settlement projects. We argue that humanity's long-term future in space will be shaped by our short-term visions for who goes there and how. Because of the way they entered the fields, we recommend avoiding the term ‘colony’ and its cognates when discussing the settlement of space, as well as other terms with similar pedigrees. We offer examples of science fiction and other writing that broaden and challenge our visions of human futures in space and SETI. In an appendix, we use an analogy with the well-funded and relatively uncontroversial searches for the dark matter particle to argue that SETI's lack of funding in the national science portfolio is primarily a problem of perception, not inherent merit. Also on arXiv: https://arxiv.org/abs/1708.05318 Please cite this version: Wright, Jason T., and Michael P. Oman-Reagan. “Visions of Human Futures in Space and SETI.” International Journal of Astrobiology, 2017, 1–12. doi:10.1017/S1473550417000222.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.011 | 0.046 |
| Scholarly communication | 0.011 | 0.016 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".