Flexible Work Before and After the Pandemic: Telecommuting, Mobility, and Work Arrangements Among Early Career Landscape Architects in the Greater Golden Horseshoe Area
Bibliographic record
Abstract
The COVID-19 pandemic is changing how landscape architects work, shifting a largely in-person, studio-based job to a work-from-home environment, and challenging longstanding office norms. This period of disruption and reflection has illuminated many perspectives on work, including that returning to pre-pandemic conditions may not be desirable for everyone. This study aims to inform the development of post-pandemic landscape architecture office policies regarding flexible work, commuting and teleworking by investigating conditions before and during the pandemic. Focused on the Greater Golden Horseshoe Area in Southern Ontario, Canada, the study employs semi-structured interviews with early-career landscape architects and managers, and finds that while some in-person office norms remain important, work can also be done well from home. Participants’ experiences were also influenced by factors like mobility modes, access to housing, and the job market. These findings led to the development of a list of seven preliminary recommendations to inform future office policy.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".