Recognising the socio-technical opportunity of workplace : An analysis of early responses to COVID-19
Bibliographic record
Abstract
COVID-19 has disrupted the ways in which we work, offering an opportunity to rethink our workplaces. Organisations have had to adapt and respond in unprecedented ways to enable continued organisational performance that have come to see many people working from home. Early responses to ‘return-to-work’ have sought to repurpose existing workspace arrangements, but they miss the unique opportunity to reconceive ‘workplace’ more comprehensively, as well as the role the property community has in enabling work. This paper aims to highlight the opportunity of viewing workplace holistically through the lens of socio-technical systems. An examination of the early responses to the pandemic identified a focus on the technical aspects of reoccupying workspaces, but taking from socio-technical systems, this should not be to the detriment of other factors. A more nuanced debate regarding who should return to work and how this will occur is presented, which highlights further a need to move beyond the physical workspace and to reflect on how we can enable ways of working.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".