New Residential Districts Ordering: from Language of Smells Description to the Space Sensory Order
Bibliographic record
Abstract
The article analyzes the sensory aspects of urban life in one of the districts in the outskirts of Moscow. Revising the concepts of sensory ordering of space, I analyze the ways how urban dwellers in this district order the space by smell perception. I define three components of sensory ordering: i) the language of sensory experience, ii) ascription of meanings to space and smells localization, iii) actions aimed at supporting the desirable olfactory landscape. The process of creating this language and negotiations about the desirable olfactory landscape are based on adopting the special terms and visualizing the smells. This language allows to interact with the various agents on different levels of power, to transform and control the space. The production of meanings, based on smells, influences the district identity. Both positive and negative smell perception produce the value of the district, while the negative smells acts differently and devalues the other city territories. Citizens actions support the sensory normativity: through sensory patrolling (different ways of detecting the smells) and microordering (creating the cleanliness and freshness within neighborhoods). These ways of ordering sensory experience and creating olfactory landscape help to explain the interaction between district dwellers, the principles of how their agency is formed, and the principles of being responsible for the space.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".