Locative Tourism Applications: Between Gaze and Performance in the Branded City
Bibliographic record
Abstract
As cities look for new ways to enliven their streets as cultural destinations, many have begun offering augmented reality tourism applications for mobile users. These apps layer audio, text, and visuals over the built environment in a bid to help tourists make sense of the city, and are a type of “locative media” - a genre of site-specific platforms that use location-aware mobile technologies to enable interplay between digital content and “real” geographies. \n \nThe maps of meaning constructed by these apps forward particular (on-brand) understandings of what is culturally valuable in the city – what sites are worth seeing, whose stories are worth listening to, how best to taste, touch, and even smell the city. However, as these apps at once animate and are animated by the streetscape they attempt to frame, gaps and seams between the urban environment and the digital layer come into focus. Along the way, users of these apps encounter other rhythms, meanings, and ways of being in the city that can trouble unifying narratives and unsettle the authority of the map. Locative media’s cartographies are not only overlaid but “entangled” with locations and their existing representations, weaving a narrative of the city that is set on a shifting stage. \n \nThis thesis draws from sensory ethnography and on-site media analysis with diverse apps in 10 cities to interrogate how these applications layer maps of meaning over the urban environment, and consider what their use – at the embodied intersection of physical and digital space – can tell us about the production of cityscapes for touristic consumption. Two comparative case studies – in Christchurch and Montreal – further examine how locative apps can mediate the urban ruin and turn the city into a screen, respectively. Situated at the intersection of urban sociology, the anthropology of the senses, cultural geography and new media studies, this study argues that exploring the performance of the locative tour offers valuable perspective on the patterns, traces, and entanglements of urban meaning making in the digital age.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".