Household Trip Patterns and Travel Characteristics in Lethbridge, Alberta
Bibliographic record
Abstract
This paper presents the results of the travel diary survey undertaken in Fall 2010 as part of the transportation master planning study in Lethbridge, Alberta. Travel diaries are invaluable in understanding the travel characteristics and patterns of the City's residents and identifying emerging trends. They provide a read on the effectiveness of the past transportation plans and programs and identify for planners what needs to be improved in the future to meet the area's transportation objectives. A total of 4,226 surveys were distributed (3,384 web, 642 mail-back and 201 onsite interviews with post-secondary students). The final number of eligible returns was 2,166 resulting in a 51% eligible return rate. The trip diary survey represents 5.29% of the study area's households (2,166 out of 40,949 households). In order to use the information to estimate trip totals by area and by time of day, the information was expanded to represent the total target population (ie. the total number of households in the study area). The household socio-economic characteristics indicated a close resemblance with Lethbridge Census data, which validates the sampling. The paper includes the sampling techniques, survey methodology, and a detailed analysis of results, and findings of the survey. For the covering asbtract of this conference see record control number 201111RT334E.
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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 | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".