Street vending in the metropolis: Proximity, distance, and emotions between migrants and tourists in Paris
Bibliographic record
Abstract
This paper focuses on the role played by migrants in the informal economy in the emblematic tourist sites of a Global North metropolis, paying heed to their interactions with tourists. It investigates the acceptability of the migrants’ presence by probing the distance or proximity of tourists to migrant vendors. Our key hypothesis is that these subaltern assert a certain right to the city by mastering interpersonal distances with others and changing the dominant meaning attached to major tourist sites. This research draws on in‐depth fieldwork carried out in four of Paris's most famous attractions: the Eiffel Tower, Notre‐Dame, Montmartre, and the Louvre. It is based on ethnographic observations, 75 interviews in five languages with tourists, and 29 interviews with actors in the informal economy, often street vendors. Analyzing this research material has allowed us to conceptualize a wide range of strategies by which migrants negotiate their place in the city. We highlight three modalities of proxemic relationships between tourists and migrants that shape the multi‐scalar emotional experiences of these sites. These complex (im)possible proximities help us better grasp how a translocal and progressive sense of place is at stake, in the very heart of a global city.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".