Interstellar Anthropology and Cultural Infrastructures for a Spacefaring Species
Bibliographic record
Abstract
This paper reflects on the role of diversity, difference, and imagination in my practice of interstellar anthropology – a method of looking beyond today’s solar system exploration and settlement toward the furthest spatial, temporal, cultural, social, and technological limits of human and non-human possibility in space. Just as astrobiology relies on informed speculation to study the nature of life in the universe, I use this interdisciplinary social scientific practice to think about our future as a spacefaring species. By combining techniques from contemporary anthropological theory, speculative fiction, ethnography, and science studies, interstellar anthropology examines the ways imaginative, social, institutional, and cultural contexts and influences are shaping interstellar exploration, and the cultural infrastructures we bring into space and will build in the future. As humanity moves into space, cultural difference and other forms of diversity will be among our most precious tools. In addition to rockets, ships, architecture, food, energy, habitats, spacesuits, and other technologies, humanity will need the kinds of cultural infrastructures that made our adaptation and survival possible here on Earth, namely differences among humans, and the imaginative possibilities produced by that diversity. Humanity’s varied languages, traditions, religions, stories, philosophies, sciences, rituals, and practices can work like a space-settlement Rosetta Stone, unlocking solutions to the challenges of possible futures here on Earth and in space. Diverse perspectives and approaches will ensure survival, adaptation, and our future as a multi-planetary and, eventually, interstellar species. Over the last century, the study of this diversity on Earth has often been the focus of the discipline of anthropology. Today, anthropologists of space continue this by studying humanity’s transformation from mostly Earth-bound to increasingly space-engaged societies.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.067 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".