Scooting around town: Determinants of shared electric scooter use in Washington D.C.
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
Personal vehicle use in North America causes a wide variety of negative externalities, although it is nonetheless still the predominant mode of transport in the region.As a result, North American cities are working to support and encourage active transport, including public transit, cycling, and walking.Privately run shared-electric-scooters (e-scooters) have rapidly grown in popularity in the United States since their launching in 2017.E-scooters are marketed as an environmentally friendly solution for various transport issues.For example, as an alternative to private vehicle short distance trips, and a solution for first-mile and last-mile to reach public transit.Furthermore, some cities in the U.S. view e-scooters as having the potential to support their transport goals, and even create pilot programs for the mode to exist legally in their cities.Yet, they have vague regulations that do not maximize the potential use of e-scooters.This thesis investigates the impact of temporal, weather, sociodemographic, land use, and transport infrastructure on e-scooter presence and variation of e-scooter presence, as well as trip distance and frequency.The research is based on publicly available data, and thus contributes a framework for studying e-scooters in North American cities that engineers, policymakers, and researchers can use to understand determinants of e-scooter use.The findings from the studies indicate that escooters are available near bicycle lanes, and that the central business district (CBD) has a significant impact on e-scooter presence.The research suggests that e-scooter trips that start or end near bicycle lanes are longer than the average e-scooter trip, as are e-scooter trips with metro stations near their destination.them, academic and otherwise, that will stay with me after graduation.I would also like to extend a special thanks to Ahmed for introducing me to the field of transport planning, which has become a passion and will guide how I seek to make a difference in the world.Thank you to Boer Cui for helping me with Chapter 2, who I also learned a great deal from!I am especially grateful for Boer's help with generating the multi-level mixed effects regression models and interpreting and discussing their results.Thank you more generally to the Transport Research at McGill (TRAM) team for being a sounding board for questions and ideas about everything from research to lunch and everything in between.Thank you also to my dear friends,
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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