The Sampling Quadrangle Assemblages Research Experiment (SQuARE) on the International Space Station, Report 1: Squares 03 and 05.
Bibliographic record
Abstract
Between January and March 2022, crew aboard the International Space Station (ISS) performed the first archaeological fieldwork in space, the Sampling Quadrangle Assemblages Research Experiment (SQuARE). The experiment aimed to: (1) develop a new understanding of how humans adapt to life in an environmental context for which we are not evolutionarily adapted, using evidence from the observation of material culture; (2) identify disjunctions between planned and actual usage of facilities on a space station; (3) develop and test techniques that enable archaeological research at a distance; and (4) demonstrate the relevance of social science methods and perspectives for improving life in space. In this article, we describe our methodology, which involves a creative re-imagining of a long-standing sampling practice for the characterization of a site, the shovel test pit.The ISS crew marked out six sample locations (“squares”) around the ISS and documented them through daily photography over a 60-day period. Here we present the results from two of the six squares: an equipment maintenance area, and an area near exercise equipment and the latrine. Using the photographs and an innovative webtool, we identified 5,438 instances of items, labeling them by type and function. We then performed chronological analyses to determine how the documented areas were actually used. Our results show differences between intended and actual use, with storage the most common function of the maintenance area, and personal hygiene activities most common in an undesignated area near locations for exercise and waste.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.004 |
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".