Speculative Space Habitats: A Future-Oriented Sensory Research-Creation Project (ETHER)
Bibliographic record
Abstract
This research explores the possibilities of sensory perception in outer space through the lens of sensory studies and futures anthropology. It includes reflections on ETHER, an immersive sensory environment designed to engage and combine the senses in novel ways. The exhibition, inspired by the immersive multi-modal installations of David Howes and Chris Salter, blends art and anthropology to craft a discernible atmosphere capable of transporting participants and introducing them to new ‘ways of sensing.’ ETHER, staged in Montreal in 2021, included video projections, aromas, drinks, and an immersive soundscape designed to engage with speculative futures through sense perception. After progressing through the exhibition, visitors participated in small group interviews where they reacted to the experience, reflected on how their sensorium was affected, and discussed themes of outer space and futurity. Sensory ethnography, an approach involving attunement to sense perception and ‘feeling along with’ research participants, constituted a guiding research method. The resulting thesis outlines the exhibition design process, discusses the unique reactions of participants to the immersive sensory environment, and reflexively considers the research-creation methods. This study ruminates on the possibilities of immersive sensory environments to engage with futures, probe the cosmic sensorium, and ultimately inspire a sense of wonder.
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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".