What about effective access to cars in motorised households?
Bibliographic record
Abstract
Most Canadian urban centres are facing difficulties with public transport systems. As car ownership has increased, urban areas have experienced a long‐term decrease in per capita ridership. At present, a significant proportion of riders in most cities is considered to be transit captives, which usually refers to carless individuals or members of carless households. But, what about members of motorised households without effective or real access to a car as, for instance, two‐income households with only one car? Do these ‘restricted car users’ constitute a significant, but somewhat hidden, segment of the transit market? The initial purpose of this paper was to learn more about individuals with restricted or no‐car access who live in car‐owning households: Who are they? Where do they live? Do their numbers fluctuate significantly throughout the day? More specifically, how has car access in motorised households changed in the past two decades? Sociospatial profiles of motorised household members with restricted car access are presented for 1981 and 1996. The second purpose was to analyse restricted car access in motorised households by using a multivariate model of car access for motorised households in the Québec metropolitan area. To achieve these objectives, we developed a logical typology of forms of ‘restricted car access’ based on a combination of variables, or resources, qualifying the degree of car access enjoyed by individuals at any given moment during the day: availability of a car, possession of a driver's licence and a driver at the disposal of other household members. This typology was then applied to the 1981 and 1996 origin–destination survey data obtained from the Québec Census Metropolitan Area.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 source (direct Gemma or distilled Codex), 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".