Tuning the Space: Investigating the Making of Atmospheres through Interior Design Practices
Bibliographic record
Abstract
This article explores the “making of atmospheres” for commercial spaces through interior design practices. Drawing upon Gernot Böhme's framework of atmospheres, it analyzes the knowledges and practices employed by interior designers when transforming an atmosphere into a “thing.” It argues that interior design is primarily a social process which renders visible the strategies of materializing the inherent elusiveness of atmospheres into the form of a concept. This concept is configured in a design-network of humans and materials and defines the conditions under which a specific intermediary status between subject and object can arise. It is also based on mechanisms of reassurance which are played out in applying a design “philosophy” and generating shared economic, cultural, and social understandings. Interior designers anticipate user experiences via images but also through specific material knowledges as a crucial form of cultural capital for “making an atmosphere.” Central human actors in the design-network are clients and their culturally informed judgments which define the boundaries of the atmospheric concept. Drawing on case study research in an interior design practice specialized in hotel design, this article argues that turning an atmosphere into a “thing” is complex and multilayered and goes beyond what is commonly subsumed under “beautification.” It suggests addressing this complexity by studying design from sociological, anthropological, and philosophical standpoints in conjunction with the practicalities of “making an atmosphere.” This approach can renew discussions around aesthetics and trigger new questions in areas like urban planning and architectural theory.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.021 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| 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".