Collecting Social Network Data to Study Social Activity-Travel Behavior: An Egocentric Approach
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents a data collection effort designed to incorporate the social dimension in social activity-travel behavior by explicitly studying the link between individuals' social activities and their social networks. The main hypothesis of the data collection effort is that individuals' travel behavior is conditional upon their social networks; that is, a key cause of travel behavior is the social dimension represented by social networks. With this hypothesis in mind, and using survey and interview instruments, the respondents' social networks are collected using an egocentric approach that is constituted by the interplay between their individual social structures and their social activity behavior. More explicitly, individuals' networks are a context within which to elicit social activity-travel generation, spatial distribution, and information communication and technology use. The resultant dataset links aspects, in novel ways, that have been rarely studied together, and provides a sound base of theory and method to study and potentially give new insights about social activity-travel behavior.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 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) | 0.000 | 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 it