Choosing between stairs and escalators in China: The impact of location, height and pedestrian volume
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
OBJECTIVE: This research examines whether Beijing residents are more or less likely than Montréal residents to avoid stair climbing, by replicating a study in Montréal, Canada that measured the impacts of distance between stairs and escalator, height between floors and pedestrian volume on stair climbing rate. METHOD: 15 stairways, 14 up-escalators and 13 down-escalators were selected in 13 publicly accessible settings in Beijing. Distance between the bottom or top of nearest stair and escalator combinations varied from 2.1 m to 114.1 m with height between floors varying from 3.3 m to 21.7 m. Simultaneous counts were conducted on stair and escalator pairs, for a total of 37,081 counted individuals. RESULTS: In the ascent model, pedestrian volume accounted for 16.3% of variance in stair climbing, 16.4% when height was added and 45.1% when distance was added. In the descent model, 40.9% of variance was explained by pedestrian volume, 41.5% when height was added and 45.5% when distance was added. CONCLUSION: Separating stairs and escalator is effective in increasing stair climbing in Beijing, accounting for 29% of the variance in stair climbing, compared with 43% in Montreal. As in the Montreal case, distance has less effect on stair use rate when descending. Overall, 25.4% of Beijingers opted for stairs when ascending compared with 20.3% of Montrealers, and for descending 32.8% and 31.1% respectively.
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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 | 0.001 | 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 it