Subtractive, ambient and bifurcated attention at work and when working from home: Towards a geography of workplace attention
Bibliographic record
Abstract
Abstract In this commentary, we draw on research on working from home during the COVID‐19 pandemic in Ontario, Canada, to expand on Bissell, Crovara, Gorman‐Murray and Straughan's (2025) paper ‘What does it mean to be present at work? Negotiating attention, distraction and presence in working from home’. We corroborate and add to their analysis of attention in relation to working from home in two ways. First, we develop further how their analysis of attention relates to social difference in working from home settings. Second, we consider through additional examples how attention relates to a working from home politics. These points lead us to push for the importance of the multiplicious theory of attention that the authors outline in their paper, against the declension narratives that often accompany solely subtractive theories of attention that they critique in their conclusion. We emphasise a theory of attention that is ambient, bifurcated, open, complex and multifaceted, as well as one that is, under certain circumstances, subtractive. We see these former ideas of attention as more central to notions of presence and better foreground the broad range of subjective experiences of work and 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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.060 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".