Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper I investigate how different modes of urban transportation shape our experience of the urban environment. My goal is to argue that how we move through a space is not merely a question of convenience or efficiency. Rather, our transportation technologies can fundamentally shift how we experience where we are. I propose a framework for considering mobility from the standpoint of phenomenological everyday aesthetics considering the social, somatic, temporal-epistemic, and affective characteristics of experience. I then suggest a typology of different forms of urban mobility distinguishing between private and public forms of transportation as well as between faster and slower modes. I next suggest a trio of factors—speed, ability to survey one’s surroundings, and ease of interruption—that play into how we experience an urban environment while discovering it by means of mobility. By applying the framework of experience and the trio of factors to the typology of transportation modes I show how each of them can foster or hinder an aesthetic experience of the urban environment. I conclude by reflecting on some further issues for investigation including the role of power in urban space, questions concerning mobility and difference (class, race, dis/ability, etc.), the place of technological mediation in urban mobility, and the role of spatial planning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it