Understanding work-arrangement choices: factors and implications
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
Information and communication technologies (ICTs) have spurred new work arrangements, yet factors influencing these choices remain unclear. This study employs mixed-logit modeling to investigate the determinants of work arrangements—’fully work-from-home (WFH),’ ‘hybrid,’ and ‘no WFH’ – and their impact on activity-travel behavior. Conducted in Halifax Regional Municipality, Nova Scotia, Canada, the study combines travel survey data with Census and built-environment data for analysis. Significant differences are found in activity count, work duration, vehicle kilometers traveled, and commute time among the work-arrangement groups. ‘Hybrid’ and ‘no WFH’ individuals tend to reside closer to downtown, while ‘full WFH’ individuals prefer suburban and rural areas. Results identify individual, household, and accessibility attributes as key determinants, confirming random heterogeneity among respondents. Results suggest shorter auto commute times correlate with higher likelihood of ‘no WFH’ and lower likelihood of ‘full WFH.’ This research aids policymakers and transportation professionals in developing effective travel demand management strategies.
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.
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 | 0.000 | 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 | 0.000 | 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) | 0.000 | 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