Assessing Impact of Carsharing on Household Car Ownership in Montreal, Quebec, Canada
Bibliographic record
Abstract
Carsharing is a service in which members of an organization have access to vehicles for predetermined periods of time (usually with short duration). One of the main impacts of this service in a city is said to be the reduction of car ownership. However, most studies used surveys of carsharing members to evaluate this effect, and these surveys may contain a bias because of the members’ interpretation of reality. This study proposes a first assessment of the reduction of car ownership in an area served by station-based carsharing service; the study used historical empirical data describing the population (Canadian census), typical travel behaviors, and car ownership (origin–destination surveys). Multiple regression models are used to study the relation between household and individual car ownership and exposure to carsharing, while controlling for other variables known to also influence ownership. Although more complex model formulations need to be tested to enhance the analysis, the results obtained in this analysis using linear regression models indicate that the number of shared vehicles in a 500-m radius is negatively correlated with car ownership.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".