Determinants of the Travel Behavior of the Suburban Elderly
Bibliographic record
Abstract
In recent years, a significant feature of population change in North American metropolitan areas has been the rapid suburbanization of elderly people. The ability to engage in routine activity may be a necessary condition for the maintenance of independent life styles and psychological well‐being among older suburbanites. Using a conceptual framework based on Parmelee and Lawton's ecological model of aging, this article offers an exploratory investigation of the determinants of the travel of separate samples of elderly male and female suburbanites to each of five destination categories of key service/activity sites in a Canadian city. The results of the tests of ten multiple regression models disclose that the levels of explanation of trip frequency afforded by “autonomy components” (e.g. health‐related characteristics, living arrangements, and income level) vary according to destination category. However, the explanatory power of “security components” (i.e. variables concerning access to destination categories) is generally low. Overall, the findings of the study provide a basis for developing a deeper understanding of the repetitive travel behavior of elderly suburbanites.
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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 | 0.001 |
| 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) | 0.001 | 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".