Evolution of Non-worker Adults’ Weekday Leisure Time Use Patterns with Focus on Information and Communication Technology in 1998, 2005, and 2010: A Canadian Perspective
Bibliographic record
Abstract
With the information and technology revolution, a vast change in travel behavior where many trips were eliminated and new trip purposes were generated was observed. Since activity travel modeling is essential for transportation planners and policy makers, many researchers’ have employed activity-based modeling to examine and study the activity participation pattern of individuals given their individual and household socio-demographic information. Among different activity purposes that have been studied in the past, there have been no studies looking at the evolution of leisure activity participation and duration change over time. New habits have emerged following the information and technology revolution that have changed the way we communicate, interact, and make decisions; therefore it is clearly important to study the trend of leisure activity participation and more specifically, the potential observed and unobserved impact of Information and Communication Technologies on adults’ participating in this activity group. The econometric framework to study the longitudinal General Social Survey dataset from Canada (between 1998 and 2010) is the Ordered Regression Duration (ORD) model. The results of this study shows that there are several significant individual and household socio-demographic variables that have an effect on Canadian Non-worker adults’ participation in in-home leisure activity purposes with focus on ICT.
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".