The Sharing Economy: Do e-scooters make the cut?
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
Sharing is as old as civilization itself. Corporations now are taking an old idea and creating a strategic model with the help of technology. This modern sharing economy, while having roots in sustainable practices, can often be mistaken as an inherently sustainable business model. We present the outcomes of a project on e-scooters as an example to emphasize the potential impacts and characteristics of a business operating within the sharing economy. To understand and gain public opinion, a survey was conducted gathering 222 responses regarding e-scooter usage in Edmonton, Alberta. Another source of information was the interview with a top executive of Lime Scooters, an e-scooter company operating in Edmonton. We found that while online platforms make resource sharing between peers easier to access, they are not always economically sustainable. Literature review on life-cycle analysis of e-scooters revealed that environmental sustainability is also not ingrained in practice, and careful consideration of business operations is needed to mitigate potentially negative impacts. In addition, thoughtful policies need to be considered and put into place in-order to encourage public and private trust. Overall, the sharing economy can be quite effective in creating a sense of community and social sustainability, but it should not be graded as a wholly sustainable practice without evidence.
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.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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