Pedestrian itinerary choice: between multi-sensory, affective and syntactic aspects of the street pattern in the historic quarter of Bejaia, Algeria
Bibliographic record
Abstract
Consideration of the five senses and emotions is not well explored in the urban environment. Different fields deal with the influence of the physical environment on human experience. However, the role of the multi-sensory experience and affectivity in selecting the itinerary for pedestrian mobility is not yet well studied. Several methods have been proposed to evaluate the correlation between pedestrian movement and the environmental configuration, where the visual parameter is the main determinant. Given that other senses could be used to select any itinerary, since the urban environment is perceived at a multisensory level, the aim of the present study is to investigate the relationship between people’s multisensory experience and their navigation in an urban environment in terms of itinerary choice. This study is carried out on the streets linking the city centre to the seafront in Bejaia, Algeria. The investigation was based on qualitative and quantitative methods. The former consists of the organised walk with running commentary technique. The latter consisted of a syntactic analysis of the street pattern. The results show that people choose their itinerary not only on the visual aspect created by the spatial configuration, but also on several variables related to the affectivity and multi-sensory experiences of the urban environment. The findings will be discussed with regard to their usefulness for the design and development of urban publics spaces.
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.
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) | 0.000 | 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".