Researching Inhabitant Agency in Interactive Architecture
Bibliographic record
Abstract
The study of Interactive Architecture (IA) spans over several decades and appears to be gaining increasing momentum in recent years. Yet, inhabitant-centered approaches towards research and design in the field still have a long way ahead to explore. Particularly, we observed that the examination of IA’s social relevance in literature is still incipient and ill supported by evidence. The study discussed in this paper is attempting to remediate this gap by exploring one of the first socio-political arguments around the relevance of IA, namely inhabitant empowerment and agency. It investigates whether an inhabitant’s relation and experience with interactive spaces, conceived according to different interaction strategies, increases the participants’ perception of their own agency in the space. In this paper, we briefly explain the prototyping of an interactive space-plan designed to emulate the behavior of four basic models of interaction. Finally, the paper presents an experimental study set to test inhabitant agency in IA. It concludes that IA has the potential to increase inhabitant agency, but that this is very dependable on the system’s design regarding behavior and interaction.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".