Action Research and Prototype Testbeds: Prioritizing Collaborative Making in Architectural Research
Bibliographic record
Abstract
As the discipline of architecture becomes ever more concerned with the development of high performance sustainable buildings and systems requiring an increasingly complex set of interrelated and closely integrated technologies, assemblies, and material methods, the questions of what forms of research approach and what project contexts might best facilitate the advancement of related research are critical.Research methods that focus on isolated and specific aspects of building science, systems engineering, or occupant interface undertaken in the highly controlled environment of the laboratory or evaluated with simulation tools have done much to advance our understanding of individual components that might comprise the next generation of high performance buildings.However, given the complexity of integrated architectural research projects that address environment, performance and interaction, requiring multiple cycles of research and development, large interdisciplinary teams, and project cycles discordant with curricular duration, new research formats may be required.Within this context, the practices of 'action research' methodologies for interdisciplinary collaboration and the construction of physical prototype testbeds as both a focus for applied research and as living laboratories for evaluation, measurement and testing, offer a compelling pairing of practice and product.The model of action research developed by humanities and educational research teams is extended and modified to develop a format applied to architectural research projects.These strategies offer specific advantage to the architectural researcher, whose work often requires methodologies outside those of traditional scientific or humanities models, and greatly benefits from what Monica Ponce de Leon has referred to as "research through making".This paper describes the organizational and logistical context of two recent design research projects (North House Prototype and The Stratus Project) in the context of an action research framework as a means to illuminate this discussion.
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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 | 0.281 | 0.269 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.013 | 0.041 |
| Scholarly communication | 0.026 | 0.045 |
| Open science | 0.011 | 0.039 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".