Evaluating the Influence of Taxi Subsidy Programs on Mitigating Difficulty Getting a Taxi in Basis of Taxi Empty-loaded Rate
Bibliographic record
Abstract
With the advent of the “Internet plus” era, a number of companies have established the service platform of taxi-hailing apps relying on the mobile Internet, which builds up a communication bridge between passengers and taxi drivers. Besides, taxi companies have initiated many subsidy programs. Based on the prediction model of passenger waiting time built in this paper, it has been proved thatthere exists a negative correlation between passenger waiting time and taxi empty-loaded rate. This paper also analyzes the influencing factors of taxi empty-loaded rate. The results show that the higher the taxi sharing rate is, the lower the taxi empty-loaded rate is. And the longer the average operation time is, the higher the taxi empty-loaded rate is. By comparing various taxi subsidy programs, this paper finally draws a conclusion that it will be much more difficult to take a taxi if taxi companies provide subsidies for passengers. But the difficulty in taking a taxi can be alleviated if taxi companies provide subsidies for taxi drivers.
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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 | 0.001 | 0.002 |
| 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 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".