Right this way: Exploring the use of mobile maps in <scp>Street‐Level</scp> wayfinding
Bibliographic record
Abstract
Abstract The poster explores practices of street‐level wayfinding mediated through the mobile digital map. To study everyday wayfinding, I approached people in the streets of Toronto, New York, Amsterdam and London, and asked for directions, requesting they draw their instructions. In total, I collected 220 drawings and corresponding observational fieldnotes, along with 20 supplemental interviews. Following collection, I used visual grounded theory (Konecki, Revija Za Socilologiju, 2011, 41, 131–160) and situational analysis (Clarke, Situational analysis: Grounded theory after the postmodern turn, 2005) to analyze the data, concentrating on encounters in which informants used a mobile mapping platform. The poster showcases a selection of the visual dataset and presents a theoretical framework for assessing the everyday applications of mobile mapping platforms such as Google Maps in relation to presumptions of reliability, seamlessness, and claims to space.
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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 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".