Change: Exploring Psychological & Sociological Constructs in the Quest for Agile Architecture & Environmental DesignChange: Exploring Psychological & Sociological Constructs in the Quest for Agile Architecture & Environmental Design
Bibliographic record
Abstract
Architecture and environmental design in our modern world proves intensely complex, driven in part through remarkable advancements in technology, in part through escalating regulatory demands, and in part by dramatic shifts in demographics, expectations and needs. Designers and developers of projects, across a range of scales, struggle to ensure relevancy, viability, potency and sustainability. To achieve such ends the exploration and application of Open Building theories and practices proves increasingly important. In reaction to static and immutable conventional environments (e.g., interiors, buildings, landscapes, etc.) Open Building and Agile Architecture methods foster a milieu of flexibility, modularity, prefabrication, adaptability and change. The critical notion of change has many dimensions, including key qualities that take account of the technological and material ethos. While the vast majority of research efforts have focused on scientific, technical and quantitative characteristics of Open Building, this paper argues that human aspects, and qualitative features, and particularly those social and psychological, are equally essential. In order for Agile Architecture to be more fully accepted, embraced and executed it is imperative that scientific/quantitative and human/qualitative facets of projects be examined, promoted and addressed in concert. A building deemed green through a checklist may fail if it is not enjoyed and accepted by users. In a similar vein, a project that embraces mutability and affords flexibility on a technical level may fail if users and stakeholders are incapable of acting, unwilling to consider, or disinterested in realizing change. Cognitive dissonance and psychological barriers, for example, may hamper a user’s readiness to transform space. NIMBYism and cynicism, for example and in the sense of the surrounding community, can likewise limit realization of more agile buildings. For Open Building and Agile Architecture to progress, there must be intense focus on a broader array of variables that, at the end of the day, prove essential to heightened acceptance, advancement and deployment. Psychology and sociology are key factors in the equation for appropriate, potent and sustainable environments. Technology matters. Above all, however, people matter.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.040 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.002 | 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".