Feeling through Images: Architectural Histories after the Emotional Turn
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
This set of Field Notes explores the emerging topic of urban emotions by foregrounding the critical role of images in mediating how built environments are experienced, interpreted, and imagined. While social histories have increasingly engaged with the ‘emotional turn,’ the spatial and visual implications of this shift remain underexplored. We argue that both still and moving images – whether artistic, journalistic, documentary, or otherwise – operate as powerful modes of representation that not only depict urban realities but also actively construct them. Their rhetorical and affective force offers a critical lens for understanding the entanglements between emotions and the built environment. Drawing insights from the 2024 workshop of the EAHN’s Urban Representations Interest Group, we outline diverse case studies that reveal how emotions such as anticipation, anxiety, outrage, longing, and detachment circulate through images and shape urban imaginaries. These contributions argue that emotional responses mediated through visual culture are integral to interpreting the built environment. By situating images at the centre of scholarly enquiries, we call for a broader methodological engagement with emotions within architectural and urban scholarship. The emotional life of images, we contend, not only enriches historical and critical analysis but also illuminates the dynamic processes through which cities are produced and reproduced.
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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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