Worker Agency versus Wellbeing in the Enforced Work-From-Home Arrangement during COVID-19: A Labour Process Analysis
Bibliographic record
Abstract
This article offers a theorization based on selected literature focused on problematizing the work-from-home phenomenon. It incorporates labour process theory and the work-from-home literature to dissect the impact of enforced working from home procedures during COVID-19. The article presents the advantages to working from home from the existing work-from-home literature and draws on labour process theory to challenge these advantages. The disadvantages discussed in this article include constant availability, enhanced productivity with unpaid labour, loss of worker subjectivity, identity conflicts, and extracting productivity while downloading costs of production to workers. While the advantages include enhanced autonomy, reduction in unproductive time and increased affordances in participation, empowerment and worker agency, the article weighs the potential, parallel impacts of worker control and reduction in personal wellbeing. Although it seems that the work-from-home arrangement is, predominantly, here to stay, I argue that workers consent to their demise, as the dark side of enforced work-from-home arrangements detract from the benefits of in-person social relations of work and learning.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| 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".